Patient classification

ABSTRACT

Clinical patient tissue samples are classified according to the physiological status of cells present in the sample. In some embodiments of the invention, such cells are classified according to their ability to respond to therapeutic agents and treatments. In other embodiments, the cells or tissue samples are classified according to their status with respect to the activity of pathways of interest. The information thus derived is useful in prognosis and diagnosis, and can further be used develop surrogate markers for disease states, and to investigate the effect of genetic polymorphisms in the responsiveness and state of cells involved in disease.

BACKGROUND OF THE INVENTION

[0001] In disease, as in health, there is a complex and changing cast ofcells playing different roles. Functional capabilities of these cellscan be altered, depending on the course of disease; as a result ofunderlying genetic differences; or due to drug exposure or othertreatments. Even cancers, sometimes characterized as simple overgrowthsof a single cell type, frequently show progression from one cell type toanother. For example, in cancers of the breast and prostate there is aclear distinction between the steroid dependent and steroid independentcells, where the latter can emerge from the course of drug treatments.Similarly, the use of chemotherapeutics can select for resistant tumorcells, which are then able to persist through treatment. In otherdiseases, such as degenerative diseases, the loss of specific cell typesis observed. For example, a key indicator of the severity of diabetes isthe number of functioning islet cells that remain.

[0002] Apart from these diseased cells, normal cells in the body may bepresent, including the mobile cells of the immune system and angiogeniccells of the vascular system. Inflammatory diseases, as well asresponses to infections, tumors and the like, are characterized by thepresence of a variety of leukocytes, including B cells, T cells,polymorphonuclear cells (eosinophils, basophils and neutrophils),macrophages, natural killer cells, megakaryocytes, and the like. Evenwithin one of these groups, there can be substantial variation in thefunction of the involved cells, for example a Th1 type T cells and a Th2type T cells can have opposite effects on the course of a disease; andgenetic and environmental effects can determine the onset and course ofT cell-mediated diseases.

[0003] Angiogenesis is a process critical to both tumor growth andmetastasis, and can be characterized by the presence of functionallydistinct endothelial cells, which can vary in their responsiveness tocytokines and other growth and regulatory factors. Although angiogenesisis a continuous process, different consecutive steps can be identified,including release of pro-angiogenic factors and proteolytic enzymes, andendothelial cell migration, morphogenesis and proliferation. Undernormal circumstances, the microvasculature is maintained in a quiescentstate. The acquisition of the angiogenic phenotype depends on theoutcome of stimulatory and inhibitory regulation by the tumur and itsmicroenvironment, features which are modified by genetic differences.

[0004] In addition to the development and localization of cells, thereis also genotypic variation, which can have important ramifications inan individuals response to therapy. Pharmacogenetics seeks to determinethe linkage between an individual's genotype and that individual'sability to metabolize or react to a therapeutic agent. The use ofpharmacogenetics is reviewed in Annu Rev Pharmacol Toxicol(2001);41:101-121. Differences in metabolism or target sensitivity canlead to severe toxicity or therapeutic failure by altering the relationbetween bioactive dose and blood concentration of the drug. However,given the complex networks of interacting elements that confer anindividuals responses to environmental or therapeutic or pathologicinfluences, simply predicting responses from genotype may be difficult.Thus, more direct means of assessing relevant patient phenotypes arerequired.

[0005] A need exists for methods that give detailed information aboutthe “physiotype”, embodying cellular events that occur in response todifferences in cell's genetic makeup, changes in a cell, itsenvironment, and other events that influence the biology of the host.The present invention satisfies this need and provides additionaladvantages.

[0006] Related Literature

[0007] Cell based assays include a variety of methods to measuremetabolic activities of cells including: uptake of tagged molecules ormetabolic precursors, receptor binding methods, incorporation oftritiated thymidine as a measure of cellular proliferation, uptake ofprotein or lipid biosynthesis precursors, the binding of radiolabeled orotherwise labeled ligands; assays to measure calcium flux, and a varietyof techniques to measure the expression of specific genes or their geneproducts.

[0008] Compounds have also been screened for their ability to inhibitthe expression of specific genes in gene reporter assays. For example,Ashby et al. U.S. Pat. No. 5,569,588; Rine and Ashby U.S. Pat. No.5,777,888 describe a genome reporter matrix approach for comparing theeffect of drugs on a panel of reporter genes to reveal effects of acompound on the transcription of a spectrum of genes in the genome.

[0009] Methods utilizing genetic sequence microarrays allow thedetection of changes in expression patterns in response to stimulus. Afew examples include U.S. Pat. No. 6,013,437; Luria et al., “Method foridentifying translationally regulated genes”; U.S. Pat. No. 6,004,755,Wang, “Quantitative microarray hybridization assays”; and U.S. Pat. No.5,994,076, Chenchik et al., “Methods of assaying differentialexpression”. U.S. Pat. No. 6,146,830, Friend et al. “Method fordetermining the presence of a number of primary targets of a drug”.

[0010] Proteomics techniques have potential for application topharmaceutical drug screening. These methods require technically complexanalysis and comparison of high resolution two-dimensional gels or otherseparation methods, often followed by mass spectrometry (for reviews seeHatzimanikatis et al. (1999) Biotechnol Prog 15(3):312-8; Blackstock etal. (1999) Trends Biotechnol 17(3):121-7. A discussion of the uses ofproteomics in drug discovery may be found in Mullner et al. (1998)Arzneimittelforschung 48(1):93-5.

SUMMARY OF THE INVENTION

[0011] Methods and compositions are provided for the classification ofclinical samples, e.g. patient tissue samples, according to thephysiological status of cells or constituents present in the sample. Theinformation thus derived is useful in prognosis and diagnosis, and canfurther be used develop surrogate markers for disease states, and toinvestigate the effect of genetic polymorphisms in the responsivenessand state of cells involved in disease. In some embodiments of theinvention, such cells are classified according to their ability torespond to therapeutic agents and treatments. In other embodiments, thecells are classified according to their status with respect to theactivity of pathways of interest. In another embodiment, patient tissuesamples are evaluated for the presence of biologically active molecules,e.g. secreted factors and the like, by adding the patient sample to acell culture responsive to the molecules.

[0012] Patient samples are cultured in a panel of environments, whereeach environment can comprise combinations of factors, cells andtherapeutically active agents. Generally at least one environmentcontains multiple factors that affect pathways of interest. The effectof altering the culture environment is assessed by monitoring multipleoutput parameters. The cells may also be treated with therapeutic agentsin the presence or absence of factors, and the profile of outputparameters determined. A sufficient number of markers are selected toprovide a high confidence level that the pathways of interest are beingmonitored. When factors are employed, a sufficient number of factors areused to involve one or a plurality of pathways and a sufficient numberof markers are determined to insure the cellular status is accuratelybeing monitored.

BRIEF DESCRIPTION OF THE DRAWINGS

[0013]FIG. 1A-B. Assay combinations for charactering cells. A.Expression of selected readout parameters on selected assay combinationsof HUVEC treated with proinflammatory cytokines. Confluent cultures ofHUVEC cells were treated with TNFα (5 ng/ml), IFNγ (200 ng/ml) and orIL-1β (1 ng/ml). After 24 hours, cultures were washed and evaluated forthe presence of the parameters ICAM-1 (1), VCAM-1 (2), E-selectin (3),IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7) by cell-based ELISA. Forthis, plates were inverted until dry, blocked with 1% Blotto for 1 hr,and treated with primary antibodies (obtained from Pharmingen and BectonDickinson) at 1 ng/ml for 1 hr. Plates were washed and secondaryperoxidase-conjugated anti-mouse IgG antibody (Promega) at 1:2500 wasapplied for 1 hr. After washing, TMB substrate (Kierkegaard & Perry) wasadded and color developed. Development was stopped by addition of H2SO4and the absorbance at 450 nm (subtracting the background absorbance at650 nm) with a Molecular Devices plate reader. The relative expressionlevels of each parameter are indicated by the OD at 450 nm shown alongthe y-axis. The mean +/− SD from triplicate samples is shown. B. Visualrepresentation of the data from FIG. 1A. The measurement obtained foreach parameter is classified according to its relative change from thevalue obtained in the optimized assay combination (containingIL-1+TNF-α+IFN-γ), and represented by shaded squares. For each parameterand assay combination, the square is shaded by a checkerboard if theparameter measurement is unchanged (<20% above or below the measurementin the first assay combination (IL-1+TNF-α+IFNγ)) or p>0.05, n=3;slanted lines indicates that the parameter measurement is moderatelyincreased (>20% but <50%); white indicates the parameter measurement isstrongly increased (>50%); vertical lines indicates that the parametermeasurement is moderated decreased (>20% but <50%); hatched linesindicates that the parameter measurement is strongly decreased (>50%less than the level measured in the first assay combination).

[0014]FIG. 2A-B. Assay combinations for characterizing cells. Confluentcultures of HUVEC cells were treated with TNFα (5 ng/ml), IFNγ (200ng/ml) and IL-1β (1 ng/ml) in the presence or absence of neutralizinganti-TNFα (R&D Systems) or control Goat anti-IgG. After 24 hours,cultures were washed and evaluated for the cell surface expression ofICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6)and MIG (7) by cell-based ELISA performed as described in FIG. 1. A. Therelative expression of each parameter is shown along the y-axis asaverage value of the OD measured at 450 nm of triplicate samples. Themean +/− SD from triplicate samples are shown. * indicates p<0.05comparing results obtained with anti-TNFα to the control. B. Visualrepresentation of the data from FIG. 2A. The measurement obtained foreach parameter is classified according to its relative change from thevalue obtained in the optimized assay combination (containingIL-1+TNF-α+IFN-γ), and represented by shaded squares. For each parameterand assay combination, the square is shaded by a checkerboard if theparameter measurement is unchanged (<20% above or below the measurementin the first assay combination (IL-1+TNF-α+IFN-γ)) or p>0.05, n=3;slanted lines indicates that the parameter measurement is moderatelyincreased (>20% but <50%); white indicates the parameter measurement isstrongly increased (>50%); vertical lines indicates that the parametermeasurement is moderated decreased (>20% but <50%); hatched linesindicates that the parameter measurement is strongly decreased (>50%less than the level measured in the first assay-combination).

[0015]FIG. 3A-C. Effect of NFκB inhibitors NHGA and PDTC, MAP kinaseinhibitor PD098059, or ibuprofen on the expression of readout parametersin the inflammatory BioMAP assay combination containing three factors(IL-1+TNF-α+IFN-γ). Confluent cultures of HUVEC cells were treated withTNFα (5 ng/ml), IFNγ (200 ng/ml) and IL-1β (1 ng/ml) in the presence orabsence of (A) 10 μM NHGA, 200 μM PDTC or 9 μM PD098059; (B) 125-500 μMibuprofen. Compounds were tested at the highest concentration at whichthey were soluble, and/or did not result in loss of cells from theplate. After 24 hours, cultures were washed and evaluated for the cellsurface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4),CD31 (5), HLA-DR (6) and MIG (7) by cell-based ELISA performed asdescribed in FIG. 1. The measurement obtained for each parameter isclassified according to its relative change from the value obtained inthe optimized assay combination (containing IL-1+TNF-α+INF-γ), andrepresented by shaded squares. For each parameter and assay combination,the square is shaded by a checkerboard if the parameter measurement isunchanged (<20% above or below the measurement in the first assaycombination (IL-1+TNF-α+INF-γ)) or p>0.05, n=3; slanted lines indicatesthat the parameter measurement is moderately increased (>20% but <50%);white indicates the parameter measurement is strongly increased (>50%);vertical lines indicates that the parameter measurement is moderateddecreased (>20% but <50%); hatched lines indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe assay combination without compounds). C. Effect of compounds on thereference readout pattern in the inflammatory BioMAP assay combinationcontaining three factors (IL-1+TNF-α+INF-γ). Confluent cultures of HUVECcells were treated with TNFα (5 ng/ml), IFNγ (200 ng/ml) and IL-1β (1ng/ml) in the presence or absence of compounds as listed in Table I.After 24 hours, cultures were washed and evaluated for the cell surfaceexpression of parameters of ICAM-1, VCAM-1, E-selectin, IL-8, CD31,HLA-DR and MIG by cell-based ELISA performed as described in FIG. 1. Theresulting BioMAPs were compared and correlation coefficients employed inclustering analysis (Clustal X program). Readout patterns are asvisualized by a tree diagram in which a) each terminal branch pointrepresents the readout pattern from one assay combination in oneexperiment; b) the length of the vertical distance from the upperhorizontal line (no change and control patterns) to the termini arerelated to the extent of difference in the readout pattern from thecontrol pattern (without drug); and c) the distance along the branchesfrom one terminal pattern value to another reflects the extent ofdifference between them. Similar patterns are thus clustered together.The figure illustrates the reproducibility of patterns resulting fromtreatment with a single drug in multiple experiments, and thoseresulting from multiple drugs that target the same signaling pathway.

[0016]FIG. 4. Assay combinations containing HUVEC and T cellco-cultures. Confluent cultures of HUVEC were incubated with media (NoCells), TNF-α, (5 ng/ml), IFN-γ (100 ng/ml) or KIT255 T cells with andwithout IL-2 (10 ng/ml) and/or IL-12 (10 ng/ml). After 24 hours cultureswere washed and evaluated for the cell surface expression of ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7)by cell-based ELISA performed as described in FIG. 1. The relativeexpression of each parameter is shown along the y-axis as average valueof the OD measured at 450 nm.BioMAP

[0017]FIG. 5A-C. Assay combinations for characterizing patient bloodsamples. Expression of selected readout parameters on selected assaycombinations of HUVEC with and without normal blood cells andproinflammatory cytokines. Human peripheral blood buffy coat cells,washed and resuspended to {fraction (1/16)} volume were added toconfluent cultures of HUVEC cells treated with TNF-α (5 ng/ml), IFN-γ(100 ng/ml), IL-1 (1 ng/ml) and or base media. After 24 hours, cultureswere washed and evaluated for the presence of the parameters ICAM-1 (1),VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6), MIG (7),CD40 (8) or MCP-1 (9) by cell-based ELISA. For this, plates were blockedwith 1% Blotto for 1 hr, and treated with primary antibodies (obtainedfrom Pharmingen and Becton Dickinson) at 1 ng/ml for 1 hr. Plates werewashed and secondary biotin-conjugated anti-mouse IgG antibody (JacksonImmunoresearch) at 1:2500 was applied for 1 hr. Plates were washed andstrepavidin-HRP (Jackson Immunoresearch) was applied for 1 hr. Afterwashing, TMB substrate (Kierkegaard & Perry) was added and colordeveloped. Development was stopped by addition of H₂SO₄ and and theabsorbance at 450 nm (subtracting the background absorbance at 650 nm)with a Molecular Devices plate reader. The relative expression levels ofeach parameter are indicated by the OD at 450 nm shown along the y-axis.A. Parameter readouts are shown from BioMAPs prepared from assaysperformed without blood or with blood and with or without one or more ofTNFα, IL-1 and/or IFNγ. B. Parameter readouts are shown from BioMAPsprepared from assays performed with (closed symbols) and without (opensymbols) blood and (a) IL-1, (b) TNFα, (c) IFNg, (d) IL1+TNF+IFNg, and(e) no added cytokine. C. Visual representation of the data from FIG.5B. The measurement obtained for each parameter is classified accordingto its relative change from the value obtained in the indicated assaycombination (containing no cytokine; IL-1, TNF-α, IFN-γ orIL-1+TNF-α+INF-γ), and represented by shaded squares. For each parameterand assay combination, the square is shaded by a checkerboard if theparameter measurement is unchanged (<20% above or below the measurementin the first assay combination) or p>0.05, n=3; slanted lines indicatesthat the parameter measurement is moderately increased (>20% but <50%);white indicates the parameter measurement is strongly increased (>50%);vertical lines indicates that the parameter measurement is moderateddecreased (>20% but <50%); hatched lines indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe assay combination without blood cells).

DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Methods and compositions are provided for the classification ofclinical samples, e.g. patient tissue samples, cells, fluids, extractsof tissues, etc., according to the physiological status of cells presentin the sample. The information thus derived is useful in prognosis anddiagnosis, including susceptibility to disease(s), status of a diseasedstate and response to changes, in the environment, such as the passageof time, treatment with drugs or other modalities. The state of thecells provided in the clinical sample may be classified according tothe-activation of pathways of interest, for example T cells can beclassified as Th1, Th2, or Th3 type cells. The cells can also beclassified as to their ability to respond to therapeutic agents andtreatments. Where the sample is being evaluated for the presence ofbiologically active molecules, the sample is added to a culture ofpotentially responsive cells, where the response of such cells is thenmonitored.

[0019] Based on changes in parameters in response to factors,information is derived that is useful in determining what pathways orcellular functionality is present in a tissue. Changes in parameters inresponse to therapeutic agents provides information that is informativeof a patient's ability to respond to a drug in the context of aphysiologically relevant microenvironment. Changes in parameters inresponse to therapeutic agents can be correlated with databases ofBioMAPs for classification or to BioMAPs from control samples. Inaddition to classification, BioMAPs derived from clinical samples andtherapeutic agents can be used to compare drugs that act on differentpathways is a physiologically relevant environment.

[0020] The clinical samples can be further characterized by geneticanalysis, proteomics, cell surface staining, or other means, in order todetermine the presence of markers that are useful in classification. Forexample, genetic polymorphisms, such as single nucleotide polymorphismsor microsatellite repeats, can be causative of disease susceptibility ordrug responsiveness, or can be linked to such phenotypes. Analysis ofthe genotype of a cell can be correlated to a BioMAP classification, and-the information used in the development of genetic markers. Similarly,such marker as expression of cell surface proteins, presence of lipids,carbohydrates, etc. can be directly or indirectly associated withdisease associated phenotypes, and with responsiveness to therapeuticagents and treatments.

[0021] The invention is also useful for screening compounds for druginteractions. Drug interactions can be problematic in cancer therapy.For example, while steroids control the edema that occurs with glioma,they also interfere with chemotherapy efficacy. Cytotoxic drugs form thebasis of many cancer therapies, thus interference with chemotherapyefficacy may offset any anti-tumor effects of angiogenesis inhibitors.Most cytotoxic drugs effect both normal and neoplastic cells, althoughat different concentrations, therefore, screening compounds in thepresence of cytotoxic drugs can be performed and reveal unexpectedinterference or beneficial synergies. Interactions between a cytotoxicdrug and any test compound is detected by the observation of BioMAPsobtained in the presence of both drugs that are inconsistent withadditive effects.

[0022] Patient samples are cultured in a panel of environments, whereeach environment can comprise combinations of factors, cells andtherapeutically active agents. Generally at least one environmentcontains multiple factors that affect pathways of interest. The effectof altering the culture environment is assessed by monitoring multipleoutput parameters. The cells may also be treated with therapeutic agentsin the presence or absence of factors, and the profile of outputparameters determined. A sufficient number of markers are selected toprovide a high confidence level that the pathways of interest are beingmonitored. When factors are employed, a sufficient number of factors areused to involve one or a plurality of pathways and a sufficient numberof markers are determined to insure the cellular status is accuratelybeing monitored.

[0023] For convenience, a clinical sample comprising cells may bereferred to as “test cells”, and will comprise one or more types ofcells present in a clinical sample. For example, a tissue sample mayinclude endothelial cells, a variety of lymphocytes and otherhematopoietic cells, tumor cells which may be clonal or polyclonal inorigin, and the like. The test cells need not be directly involved in adisease of interest.

[0024] A clinical sample may also be evaluated for the presence ofbiologically active factors and other molecules, where such non-cellularmaterial is indicative of the physiological state of the tissue fromwhich it is obtained. Such samples are evaluated for their effect on oneor a panel of cells, as described in co-pending patent application09/800,605.

[0025] The term “assay combinations” refers to such cultures, where testcells are contacted with medium and multiple combination of factors,agents and other culture variations. These cell cultures are created bythe addition of a sufficient number of different factors to provoke aresponse that simulates cellular physiology of a state of interest, andto allow for the status of cells in culture to be determined in relationto a change in an environment. The state of interest will normallyinvolve a plurality of pathways where the pathways regulate a pluralityof parameters or markers identifying a phenotype associated with thestate of interest. In a preferred embodiment, one or more assaycombinations are provided that simulate physiological cell states ofinterest, particularly physiological cell states in vivo, usually usingthe same type of cells or combinations, of cells. Such a simulation willusually include at least three different regulated features (parameters)shared with in vivo cell counterparts in normal or diseased states.Alternatively, the simulation will include a cell culture system thatallows discrimination of modifications in at least three differentsignaling pathways or cell functions operative in vivo under conditionsof interest.

[0026] A phenotype of the test cells that is useful for monitoringoutput parameters can be generated by including a plurality of factors,and optionally additional cells, e.g. stromal cells, endothelial cells,fibroblasts, etc., that may interact with the patient tissue. Thefactors and cells inducing pathways induce a response in the test cellsin vitro. Such factors are naturally occurring compounds, e.g. knowncompounds that have surface membrane receptors and induce a cellularsignal that results in a modified phenotype; or synthetic compounds thatmimic such naturally occurring factors. In some instances, factors willact intracellularly by passing through the cell surface membrane andentering the cytosol with binding to components in the cytosol, nucleusor other organelle. In referring to factors, it is understood that it isthe activities of the factors that are of interest and not necessarily aparticular naturally occurring factor itself.

[0027] For each test cell there are a number of markers that can bemeasured, which relate to specific pathways associated with the celltype and condition. As described in co-pending U.S. patent applicationNo. 09/800,605, which disclosure is specifically incorporated byreference, at least about 4 markers are identified that allow forevaluating the up or down regulation of at least 2 pathways, generallythree or more pathways, where the total number of markers will usuallynot exceed 8. The markers are selected to provide a robust picture ofthe status of the cell, due to its condition, e.g. pro-inflammatory,immunosuppressive, neoplastic, etc., its response to therapy, itsresponse to a drug, or the like. Each set of markers will define a setof cell pathways and their response. However, there will normally be atleast 2, usually at least 3, common markers for the particulardetermination.

[0028] The nature and number of parameters measured generally reflectsthe response of a plurality of pathways. The subject approach providesfor robust results having enhanced predictability in relation to thestatus of the test cells. The results may be compared to the basalcondition, tissue matched normal controls, and/or the condition in thepresence of one or more of the factors, particularly in comparison toall of the factors used in the presence and absence of agent. Theeffects of different environments are conveniently provided in BioMAPs,where the results can be mathematically compared.

BioMAP

[0029] A BioMAP is prepared from values obtained by measuring parametersor markers of the test cells in the presence and absence of differentfactors, and/or by comparing the presence of an agent of interest and atleast one other state, usually the control state, which may include thestate without agent or with a different agent. Parameters includecellular products or epitopes thereof, as well as functional states,whose levels vary in the presence of the factors. Desirably, the resultsare normalized against a standard, usually a “control value or state,”to provide a normalized data set. Values obtained from test conditionscan be normalized by subtracting the unstimulated control values fromthe test values, and dividing the corrected test value by the correctedstimulated control value. Other methods of normalization can also beused; and the logarithm or other derivative of measured values or ratioof test to stimulated or other control values may be used. Data isnormalized to control data on a cell type under control conditions, buta BioMAP may-comprise normalized data from one, two or multiple celltypes and assay conditions.

[0030] By referring to a BioMAP is intended that the dataset willcomprise values of the levels of at least two sets of parametersobtained under different assay combinations. Depending on the use of theBioMAP, the BioMAP may also include the parameter values for each thefactors included in the assay combination, individually and/or togetherwith fewer than the entire assay combination. The parameter values areusually created electronically and stored in a data processor forcomparison with other BioMAPs and databases compiled from the BioMAPs.

[0031] A graph of a BioMAP can be presented visually as numericalvalues, symbols, color gradations, or the like, indicating the parametervalues. The graph is conveniently presented where color and/or designprovide an indication of the level of the particular marker. Theindicators may be vertical or horizontal as to the individual markersand the assay combinations, so that by looking at the graph, one canimmediately compare the levels of the different markers for each of thecombinations and discern patterns related to the assay combinations andthe differences between assay combinations. In this way, one can rapidlyrelate different candidate pharmacologic agents, the pathways theyaffect and their efficacy in modulating the individual pathways.

[0032] Optionally, a BioMAP can be annotated to indicate informationabout the sources of information for the dataset. Annotations mayinclude, for example, the number of assay conditions in a panel (n);controls used for normalization (N); parameters (P), which may bedesignated for the number and identity of the parameters; environmentalchanges, such as the addition of factors and/or agents or a change inthe physical conditions (V); cell type (C); and the like. The annotationmay further specify specific factors or conditions present in one of theassay combinations, e.g. n1, n2, n3, etc., where the presence of factorsin the assay combination is designated (F), temperature may bedesignated (T), pH, etc. The parameters may also be designated in thisas, e.g. P1=ICAM-1, P2=VCAM-1, P3=E-selectin, etc. Written out, theannotation may be set forth as: (v) B {n; N; P; C; F}.

[0033] A database of BioMAPs can be compiled from sets of experiments,for example, a database can contain BioMAPs obtained from clinicalsamples such as sites of inflammation, tumors, etc., each in a panel ofassay combinations, with multiple different environmental changes, whereeach change can be a series of related compounds, or compoundsrepresenting different classes of molecules. In another embodiment, adatabase comprises BioMAPs from one compound, with multiple differentcell panels.

[0034] Mathematical systems can be used to compare BioMAPs, and toprovide quantitative measures of similarities and differences betweenthem. For example, the BioMAPs in the database can be analyzed bypattern recognition algorithms or clustering methods (e.g. hierarchicalor k-means clustering, etc.) that use statistical analysis (correlationcoefficients, etc.) to quantify relatedness of BioMAPs. These methodscan be modified (by weighting, employing classification strategies,etc.) to optimize the ability of a BioMAP to discriminate differentfunctional effects. For example, individual parameters can be given moreor less weight when analyzing the dataset of the BioMAP, in order toenhance the discriminatory ability of the BioMAP. The effect of alteringthe weights assigned each parameter is assessed, and an iterativeprocess is used to optimize pathway or cellular function discrimination.

[0035] In many cases the literature has sufficient information toestablish assay combinations to provide a useful BioMAP. Where theinformation is not available, by using the procedures described in theliterature for identifying markers for diseases, microarrays for RNAtranscription comparisons, proteomic or immunologic comparisons, betweennormal cells and cells in the disease state, one can ascertain theendogenous factors associated with the disease state and the markersthat are produced by the cells associated with the disease state.

[0036] Biomap analysis can be used to optimize cell culture conditions.Additional markers can be deduced and added as a marker to the map. Thegreater the number of individual markers that vary independently of eachother, the more robust the BioMAP. If desired, the parameters of theBioMAP can be optimized by obtaining BioMAP parameters within an assaycombination or panel of assay combinations using different sets ofreadout, and using pattern recognition algorithms and statisticalanalyses to compare and contrast different BioMAPs of differentparameter sets. Parameters are selected that provide a BioMAP thatdiscriminates between changes in the environment of the cell cultureknown to have different modes of action, i.e. the BioMAP is similar foragents with a common mode of action, and different for agents with adifferent mode of action. The optimization process allows theidentification and selection of a minimal set of parameters, each ofwhich provides a robust readout, and that together provide a BioMAP thatenables discrimination of different modes of action of stimuli oragents. The iterative process focuses on optimizing the assaycombinations and readout parameters to maximize efficiency and thenumber of signaling pathways and/or functionally different cell statesproduced in the assay configurations that can be identified anddistinguished, while at the same time minimizing the number ofparameters or assay combinations required for such discrimination.

Clinical Samples

[0037] Clinical samples for use in the methods of the invention may beobtained from a variety of sources, including blood, lymph,cerebrospinal fluid, synovial fluid, tissue biopsies, skin, saliva,lavage, and the like. Such samples can comprise complex populations ofcells, which can be assayed as a population, or separated intosub-populations, and can also comprise acellular samples. Such cellularand acellular sample can be separated by centrifugation, elutriation,density gradient separation, apheresis, affinity selection, panning,FACS, centrifugation with Hypaque, etc. By using antibodies specific formarkers identified with particular cell types, a relatively homogeneouspopulation of cells may be obtained. Alternatively, a heterogeneous cellpopulation can be used. Acellular samples can be separated according toimmunologic or biochemical criteria, for example by variouselectrophoretic and chromatographic means, as is known in the art.

[0038] Once a sample is obtained, it can be used directly, frozen, ormaintained in appropriate culture medium for sport periods of time.Various media can be employed to maintain cells during theclassification process. There are established protocols for the cultureof diverse cell types that reflect their in vivo counterparts. Protocolsmay require the use of special conditions and selective media to enablecell growth or expression of specialized cellular functions.

[0039] Such methods are described in the following: Animal Cell CultureTechniques (Springer Lab Manual), Clynes (Editor), Springer Verlag,1998; Animal Cell Culture Methods (Methods in Cell Biology, Vol 57,Barnes and Mather, Eds, Academic Press, 1998; Harrison and Rae, GeneralTechniques of Cell Culture (Handbooks in Practical Animal Cell Biology),Cambridge University Press, 1997; Endothelial Cell Culture (Handbooks inPractical Animal Cell Biology), Bicknell (Editor), Cambridge UniversityPress, 1996; Human Cell Culture, Cancer Cell Lines Part 1: Human CellCulture, Masters and Palsson, eds., Kluwer Academic Publishers, 1998;Human Cell Culture Volume II—Cancer Cell Lines Part 2 (Human CellCulture Volume 2), Masters and Palsson, eds., Kluwer AcademicPublishers, 1999; Wilson, Methods in Cell Biology: Animal Cell CultureMethods (Vol 57), Academic Press, 1998; Current Protocols in Immunology,Coligan et al., eds, John Wiley & Sons, New York, N.Y., 2000; CurrentProtocols in Cell Biology, Bonifacino et al., eds, John Wiley & Sons,New York, N.Y., 2000.

[0040] The methods of the invention find use in a wide variety of animalspecies, including mammalian species. Animal models, particularly smallmammals, e.g. murine, lagomorpha, etc. are of interest for experimentalinvestigations. Humans are of particular interest for both diagnosticand prognostic applications of the method.

[0041] The samples may come from any organ or compartment of the body,to the extent the cells can be obtained by any convenient procedure,such as the drawing of blood, venipuncture, biopsy, or the like. Celltypes that can find use in the subject invention, include endothelialcells, muscle cells, myocardial, smooth and skeletal muscle cells,mesenchymal cells, epithelial cells; hematopoietic cells, such, aslymphocytes, including T-cells, such as Th1 T cells, Th2 T cells, Th0 Tcells, cytotoxic T cells; B cells, pre-B cells, etc.; monocytes;dendritic cells; neutrophils; and macrophages; natural killer cells;mast cells;, etc.; adipocytes, cells involved with particular organs,such as thymus, endocrine glands, pancreas, brain, such as neurons,glia, astrocytes, dendrocytes, etc. and in some instances, may eveninvolve genetically modified cells thereof. Hematopoietic cells will beassociated with inflammatory processes, autoimmune diseases, etc.,endothelial cells, smooth muscle cells, myocardial cells, etc. may beassociated with cardiovascular diseases; almost any type of cell may beassociated with neoplasias, such as sarcomas, carcinomas and lymphomas;liver diseases with hepatic cells; kidney diseases with kidney cells;etc. Usually a sample will comprise at least about 10² cells, moreusually at least about 10³ cells, and preferable 10⁴ or more cells.

Assay Combinations

[0042] The term “environment,” or “culture condition”, as used in theassay combinations of the subject methods encompasses cells, media,factors, time and temperature. Environments may also include drugs andother compounds, particular atmospheric conditions, pH, saltcomposition, minerals, etc. The conditions will be controlled and theBioMAP will reflect the similarities and differences between each of theassay combinations involving a different environment or culturecondition.

[0043] Culture of cells is typically performed in a sterile environment,for example, at 37° C. in an incubator containing a humidified 92-95%air/5-8% CO₂ atmosphere. Cell culture may be carried but in nutrientmixtures containing undefined biological fluids such as fetal calfserum, or media which is fully defined and serum free.

[0044] Culture protocols may require the use of special conditions andselective media to enable cell growth or expression of specializedcellular functions. Such methods are described in the following: AnimalCell Culture Techniques (Springer Lab Manual), Clynes (Editor), SpringerVerlag, 1998; Animal Cell Culture Methods (Methods in Cell Biology, Vol57, Barnes and Mather, Eds, Academic Press, 1998; Harrison and Rae,General Techniques of Cell Culture (Handbooks in Practical Animal CellBiology), Cambridge University Press, 1997; Endothelial Cell Culture(Handbooks in Practical Animal Cell Biology), Bicknell (Editor),Cambridge University Press, 1996; Human Cell Culture, Cancer Cell LinesPart 1: Human Cell Culture, Masters and Palsson, eds., Kluwer AcademicPublishers, 1998; Human Cell Culture Volume II—Cancer Cell Lines Part 2(Human Cell Culture Volume 2), Masters and Palsson, eds., KluwerAcademic Publishers, 1999; Wilson, Methods in Cell Biology: Animal CellCulture Methods (Vol 57), Academic Press, 1998; Current Protocols inImmunology, Coligan et al., eds, John Wiley & Sons, New York, N.Y.,2000; Current Protocols in Cell Biology, Bonifacino et al., eds, JohnWiley & Sons, New York, N.Y., 2000.

[0045] Some preferred environments include environments thatdiscriminate or emphasize cell or tissue states associated withpathology in one or more diseases, for example, Th1 versus Th2polarization of effector T cells; prothrombotic; inflammatory (e.g.NFκB, upregulated TNF-α cytokine production, downregulated IL-10, TGFβ,etc.; dysregulated proliferation (neoplasia); angiogenesis; etc.)Environments that facilitate discrimination of specific signalingpathways implicated in disease states are also of interest, e.g. NFκB,classic Th1 or Th2 induction environments, etc.

[0046] A assay combinations are used in classifying and investigatingcomplex states of cells, frequently resulting from cellularinteractions, which may frequently involve at least about two,frequently three, or more different cell types and/or will involve aplurality of soluble factors that are present in a physiological fluid,particularly as the result of a physiological event, e.g. infection,neoplasia, autoimmune, etc. that is, frequently involving more than onecell type and more than one factor. The measured parameters may beobtained from one or more of the cell types. The cells in the assaycombination, either one or up to each of the different cell types, canhave identifying characteristics allowing them to be distinguishedduring analysis. Various techniques may be employed to identify thecells in the assay combination for analysis of the parameters ofinterest.

[0047] Conditions of interest include inflammatory processes that occurin response to infection, trauma, etc., autoimmune diseases, such asdiabetes, lupus, arthritis, etc., cardiovascular diseases, such asstroke, atherosclerosis, etc., neoplasia, hyperplasia, addiction,infection, obesity, cellular degeneration, apoptosis, senescence,differentiation, and the like.

[0048] Multifactorial, usually involving multicellular, assaycombinations, may reflect many of the conditions indicated above, suchas inflammatory processes; autoimmune diseases; cardiovascular diseases;tumors, etc. That is, a multiplicity of factors are employed toinfluence a plurality of cellular pathways and a multiplicity ofparameters are measured that reflect the status of the pathways.Degenerative diseases, including affected tissues and surrounding areas,may be exploited to determine both the response of the affected tissue,and the interactions with other cell types or other parts of the body.

[0049] Factors added to the cultures can be the products of other celltypes, for example, expressed proteins associated with a disease, can becompounds that simulate naturally occurring factors, can be surfacemembrane proteins free of the membrane or as part of microsomes, orother reagent that induces the appropriate pathway to aid in thesimulation of the phenotype or provides the appropriate environment tosimulate the physiological condition. Factors (including mimeticsthereof) can be added individually or in combination, from feeder cells,may be added as a bolus or continuously, where the factor is degraded bythe culture, etc.

[0050] Illustrative naturally occurring factors include cytokines,chemokines, and other factors, e.g. growth factors, such factors includeGM-CSF, G-CSF, M-CSF, TGF, FGF, EGF, TNF-α, GH, corticotropin,melanotropin, ACTH, etc., extracellular matrix components, surfacemembrane proteins, such as integrins and adhesins, and other componentsthat are expressed by the targeted cells or their surrounding milieu invivo, etc., that may be isolated from natural sources or produced byrecombinant technology or synthesis, compounds that mimic the action ofother compounds or cell types, e.g. an antibody which acts like a factoror mimics a factor, such as synthetic drugs that act as ligands fortarget receptors. For example, in the case of the T cell receptor, theaction of an oligopeptide processed from an antigen and presented by anantigen-presenting cell, etc. can be employed. Where a family of relatedfactors are referred to with a single designation, e.g. IL-1, VEGF, IFN,etc., in referring to the single description, any one or some or all ofthe members of the group are intended, where the literature will beaware of how the factors are to be used in the context of the assaycombination. Components may also include soluble, or immobilizedrecombinant or purified receptors, or antibodies against receptors orligand mimetics.

[0051] Cancer cells may be cultured with different factors based on thedifferent cells in the environment of the tumor, as well as otherfactors in the blood induced by factors secreted by the neoplasticcells. Many of these factors will be the same factors described above,but additional factors include factors associated with angiogenesis,such as angiogenin, angiopoietin-1, HGF, PDGF, TNF-α, VEGF, IL-1, IL-4,IL-6, IL-8 and fibronectin.

Panels

[0052] For the most part, the BioMAP dataset will comprise data from apanel of assay combinations. The panel will be related to the purpose ofthe BioMAP and may include not only the information that has beendeveloped substantially concurrently with the study, but alsoinformation that has been previously developed under comparableconditions. Frequently a panel will be used that is comprised of atleast one assay combination that provides for simulation of multiplepathways of interest, while other assay combinations in the panel arevariants thereof. The number of combinations in a panel may vary withthe particular use. For example, the minimum number of assaycombinations will be two for a panel for initial screening that wouldcomprise a single assay combination. A panel for characterizing themechanism of action of an active compound will usually comprise aplurality of assay combinations, usually at least about 4, more usuallyat least 6, frequently at least about 10 and may be as many as 20 ormore unique combinations.

[0053] In another embodiment, the panel comprises culture conditionswhere multiple specific changes are made to the culture environment,e.g. two or more changes, usually not more than about 6, more usuallynot more than about 4. Such changes are associated with the additionalinformation that is engendered by the indicated variations. Thevariations can include the addition of known inhibitors of specificpathways.

Parameters

[0054] Parameters are quantifiable components of cells, particularlycomponents that can be accurately measured, desirably in a highthroughput system. A parameter can be any cell component or cell productincluding cell surface determinant, receptor, protein or conformationalor posttranslational modification thereof, lipid, carbohydrate, organicor inorganic molecule, nucleic acid, e.g. mRNA, DNA, etc. or a portionderived from such a cell component or combinations thereof. While mostparameters will provide a quantitative readout, in some instances asemi-quaptitative or qualitative result will be acceptable. Readouts mayinclude a single determined value, or may include mean, median value orthe variance, etc. Characteristically a range of parameter readoutvalues will be obtained for each parameter from a multiplicity of thesame assay combinations, usually at least about 2 of the same assaycombination will be performed to provide a value. Variability isexpected and a range of values for each of the set of test parameterswill be obtained using standard statistical methods with a commonstatistical method used to provide single values.

[0055] Markers are selected to serve as parameters based on thefollowing criteria, where any parameter need not have all of thecriteria: the parameter is modulated in the physiological condition thatone is simulating with the assay combination; the parameter is modulatedby a factor that is available and known to modulate the parameter invitro analogous to the manner it is modulated in vivo; the parameter hasa robust response that can be easily detected and differentiated and isnot too sensitive to concentration variation, that is, it will notsubstantially differ in its response to an over two-fold change; theparameter is secreted or is a surface membrane protein or other readilymeasurable component; the parameter desirably requires not more than twofactors to be produced; the parameter is not co-regulated with anotherparameter, so as to be redundant in the information provided; and insome instances, changes in the parameter are indicative of toxicityleading to cell death. The set of parameters selected is sufficientlylarge to allow distinction between reference patterns, whilesufficiently selective to fulfill computational requirements.

[0056] For each assay combination, certain parameters will befunctionally relevant and will be altered in response to test orreference agents or conditions, while other parameters may remain staticin that particular combination. Biomaps will generally comprise onlyfunctionally relevant parameter information, although a static parametermay serve as an internal control. A typical BioMAP will comprise datafrom at least 3 functionally relevant parameters, more usually at leastabout 5 functionally, relevant parameters, and may include 10 or morefunctionally relevant parameters, usually not more than about 30, moreusually not more than about 20, parameters. In analyzing the data fromthe BioMAP, all of the parameters need not be weighed equally. Thoseparameters that are closely functionally associated with the diseasestate or pathophysiologic response, and/or with modulation of cellpathways of interest may be given greater weight in evaluating acandidate drug or a readout, as compared to other parameters that aresuggestive, but do not have as strong an association.

[0057] Parameters of interest include detection of cytoplasmic, cellsurface or secreted biomolecules, frequently biopolymers, e.g.polypeptides, polysaccharides, polynucleotides, lipids, etc. Cellsurface and secreted molecules are a preferred parameter type as thesemediate cell communication and cell effector responses and can be morereadily assayed. In one embodiment, parameters include specificepitopes. Epitopes are frequently identified using specific monoclonalantibodies or receptor probes. In some cases the molecular entitiescomprising the epitope are from two or more substances and comprise adefined structure; examples include combinatorially determined epitopesassociated with heterodimeric integrins. A parameter may be detection ofa specifically modified protein or oligosaccharide, e.g. aphosphorylated protein, such as a STAT transcriptional protein; orsulfated oligosaccharide, or such as the, carbohydrate structure SialylLewis x, a selectin ligand. The presence of the active conformation of areceptor may comprise one parameter while an inactive conformation of areceptor may comprise another, e.g. the active and inactive forms ofheterodimeric integrin ∀_(m)∃₂ or Mac-1.

[0058] A parameter may be defined by a specific monoclonal antibody or aligand or receptor binding determinant. Parameters may include thepresence of cell surface molecules such as CD antigens (CD1-CD247), celladhesion molecules including α₄β₇ and other integrins, selectin ligands,such as CLA and Sialyl Lewis x, and extracellular matrix components.Parameters may also include the presence of secreted products such aslymphokines, including IL-2, IL-4, IL-6, growth factors, etc. (LeukocyteTyping VI, T. Kishimoto et al., eds., Garland Publishing, London,England, 1997); Chemokines in Disease: Biology and Clinical Research(Contemporary Immunology), Hebert, Ed., Humana Press, 1999.

[0059] For activated T cells these parameters may include IL-1R, IL-2R,IL4R, IL-12Rβ, CD45RO, CD49E, tissue selective adhesion molecules,homing receptors, chemokine receptors, CD26, CD27, CD30 and otheractivation antigens. Additional parameters that are modulated duringactivation include MHC class II; functional activation of integrins dueto clustering and/or conformational changes; T cell proliferation andcytokine production, including chemokine production. Of particularimportance is the regulation of patterns of cytokine production, thebest-characterized example being the production of IL-4 by Th2 cells,and interferon-γ by Th1 T cells. The ability to shift cytokineproduction patterns in vivo is a powerful means of modulating pathologicimmune responses, for example in models of EAE, diabetes, inflammatorybowel disease, etc. Thus, the expression of secreted cytokines may be apreferred class of parameters, detectable, for example, by ELISAanalysis of the supernatants, etc.

Therapeutic Agents

[0060] In many cases, it will be of interest to determine whether apatient is responsive to a particular therapeutic agent or regimen. Inparticular, it is of interest to determine the efficacy of suchtherapies in a biologically relevant context, i.e. in the presence offactors and interacting cells. Included are pharmacologically activedrugs, genetically active molecules, etc. Compounds of interest includechemotherapeutic agents, anti-inflammatory agents, hormones or hormoneantagonists, ion channel modifiers, and neuroactive agents. Exemplary ofpharmaceutical agents suitable for this invention are those describedin, “The Pharmacological Basis of Therapeutics,” Goodman and Gilman,McGraw-Hill, New York, N.Y., (1996), Ninth edition, under the sections:Drugs Acting at Synaptic and Neuroeffector Junctional Sites; DrugsActing on the Central Nervous System; Autacoids: Drug Therapy ofInflammation; Water, Salts and Ions; Drugs Affecting Renal Function andElectrolyte Metabolism; Cardiovascular Drugs; Drugs AffectingGastrointestinal Function; Drugs Affecting Uterine Motility;Chemotherapy of Parasitic Infections; Chemotherapy of MicrobialDiseases; Chemotherapy of Neoplastic Diseases; Drugs Used forImmunosuppression; Drugs Acting on Blood-Forming organs; Hormones andHormone Antagonists; Vitamins, Dermatology; and Toxicology, allincorporated herein by reference.

Classification Methods

[0061] Cells and samples are classified by adding a therapeutic agent ortreatment; and/or by culturing cells in combinations of factors, in atleast one and usually a plurality of assay combinations to form a panelof assay combinations, usually in conjunction with positive and negativecontrols. The change in parameter readout in response to an agent,sample or factors is measured, desirably normalized, and the resultingBioMAP may then be evaluated by comparison to reference BioMAPs. Thereference BioMAPs may include basal readouts in the presence and absenceof the factors, BioMAPs obtained with other agents, which may or may notinclude known inhibitors of known pathways, etc. Agents of interest foranalysis include any biologically active molecule with the capability ofmodulating, directly or indirectly, the phenotype of interest of a cellof interest.

[0062] The agents are conveniently added in solution, or readily solubleform, to the medium of cells in culture. The agents may be added in aflow-through system, as a stream, intermittent or continuous, oralternatively, adding a bolus of the compound, singly or incrementally,to an otherwise static solution. In a flow-through system, two fluidsare used, where one is a physiologically neutral solution, and the otheris the same solution with the test compound added. The first fluid ispassed over the cells, followed by the second. In a single solutionmethod, a bolus of the test compound is added to the volume of mediumsurrounding the cells. The overall concentrations of the components ofthe culture medium should not change significantly with the addition ofthe bolus, or between the two solutions in a flow through method.

[0063] Preferred agent formulations do not include additionalcomponents, such as preservatives, that may have a significant effect onthe overall formulation. Thus preferred formulations consist essentiallyof a biologically active compound and a physiologically acceptablecarrier, e.g. water, ethanol, DMSO, etc. However, if a compound isliquid without a solvent, the formulation may consist essentially of thecompound itself.

[0064] A plurality of assays may be run in parallel with different agentconcentrations to obtain a differential response to the variousconcentrations. As known in the art, determining the effectiveconcentration of an agent typically uses a range of concentrationsresulting from 1:10, or other log scale, dilutions. The concentrationsmay be further refined with a second series of dilutions, if necessary.Typically, one of these concentrations serves as a negative control,i.e. at zero concentration or below the level of detection of the agentor at or below the concentration of agent that does not give adetectable change in the phenotype.

[0065] Various methods can be utilized for quantifying the presence ofthe selected markers. For measuring the amount of a molecule that ispresent, a convenient method is to label a molecule with a detectablemoiety, which may be fluorescent, luminescent, radioactive,enzymatically active, etc., particularly a molecule specific for bindingto the parameter with high affinity Fluorescent moieties are readilyavailable for labeling virtually any biomolecule, structure, or celltype. Immunofluorescent moieties can be directed to bind not only tospecific proteins but also specific conformations, cleavage products, orsite modifications like phosphorylation. Individual peptides andproteins can be engineered to autofluoresce, e.g. by expressing them asgreen fluorescent protein chimeras inside cells (for a review see Joneset al. (1999) Trends Biotechnol. 17(12):477-81). Thus, antibodies can begenetically modified to provide a fluorescent dye as part of theirstructure

[0066] The use of high affinity antibody binding and/or structurallinkage during labeling provides dramatically reduced nonspecificbackgrounds, leading to clean signals that are easily detected. Suchextremely high levels of specificity enable the simultaneous use ofseveral different fluorescent labels, where each preferably emits at aunique color. Fluorescence technologies have matured to the point wherean abundance of useful dyes are now commercially available. These areavailable from many sources, including Sigma Chemical Company (St. LouisMo.) and Molecular Probes (Handbook of Fluorescent Probes and ResearchChemicals, Seventh Edition, Molecular Probes, Eugene Oreg.). Otherfluorescent sensors have been designed to report on biologicalactivities or environmental changes, e.g. pH, calcium concentration,electrical potential, proximity to other probes, etc. Methods ofinterest include calcium flux, nucleotide incorporation, quantitativePAGE (proteomics), etc.

[0067] Highly luminescent semiconductor quantum dots (zincsulfide-capped cadmium selenide) have been covalently coupled tobiomolecules for use in ultrasensitive biological detection (Stupp etal. (1997) Science 277(5330):1242-8; Chan et al. (1998) Science281(5385):2016-8). Compared with conventional fluorophores, quantum dotnanocrystals have a narrow, tunable, symmetric emission spectrum and arephotochemically stable (Bonadeo et al. (1998) Science 282(5393):1473-6).The advantage of quantum dots is the potential for exponentially largenumbers of independent readouts from a single source or sample.

[0068] Multiple fluorescent labels can be used on the same sample andindividually detected quantitatively, permitting measurement of multiplecellular responses simultaneously. Many quantitative techniques havebeen developed to harness the unique properties of fluorescenceincluding: direct fluorescence measurements, fluorescence resonanceenergy transfer (FRET), fluorescence polarization or anisotropy (FP),time resolved fluorescence (TRF), fluorescence lifetime measurements(FLM), fluorescence correlation spectroscopy (FCS), and fluorescencephotobleaching recovery (FPR) (Handbook of Fluorescent Probes andResearch Chemicals, Seventh Edition, Molecular Probes, Eugene Oreg.).

[0069] Depending upon the label chosen, parameters may be measured usingother than fluorescent labels, using such immunoassay techniques asradioimmunoassay (RIA) or enzyme linked immunosorbance assay (ELISA),homogeneous enzyme immunoassays, and related non-enzymatic techniques.These techniques utilize specific antibodies as reporter molecules,which are particularly useful due to their high degree of specificityfor attaching to a single molecular target. U.S. Pat. No. 4,568,649describes ligand detection systems, which employ scintillation counting.These techniques are particularly useful for protein or modified proteinparameters or epitopes, or carbohydrate determinants. Cell readouts forproteins and other cell determinants can be obtained using fluorescentor otherwise tagged reporter molecules. Cell based ELISA or relatednon-enzymatic or fluorescence-based methods enable measurement of cellsurface parameters and secreted parameters. Capture ELISA and relatednon-enzymatic methods usually employ two specific antibodies or reportermolecules and are useful for measuring parameters in solution. Flowcytometry methods are useful for measuring cell surface andintracellular parameters, as well as shape change and granularity andfor analyses of beads used as antibody- or probe-linked reagents.Readouts from such assays may be the mean fluorescence associated withindividual fluorescent antibody-detected cell surface molecules orcytokines, or the average fluorescence intensity, the medianfluorescence intensity, the variance in fluorescence intensity, or somerelationship among these.

[0070] As an example, Luminex beads or other fluorescent beads, or beadsvarying in light scattering parameters can be conjugated to antibodiesto cytokines or other parameters, or conjugated to protein receptors forparameters. The conjugated beads are added to the cells, cell lysate, orto the removed supernatant, allowing bead binding to target parameters.Also, fluorescent antibody to a distinct epitope of the target parameteris used to measure the level of target parameter bound. The fluorescenceand light scatter characteristics of the beads constitute an identifiedof the target parameter, and fluorescence derived from added antibody tothe target parameter is an indication of the quantity of targetparameter bound, and hence a readout of the individual parameter.

[0071] Flow cytometry may be used to quantitate parameters such as thepresence of cell surface proteins or conformational or posttranslationalmodification thereof; intracellular or secreted protein, wherepermeabilization allows antibody (or probe) access, and the like.Brefeldin A is commonly utilized to prevent secretion of intracellularsubstances. Flow cytometry methods are known in the art, and describedin the following: Flow Cytometry and Cell Storing (Springer Lab Manual),Radbruch, Ed., Springer Verlag, 2000; Ormerod, Flow Cytometry, SpringerVerlag, 1999; Flow Cytometry Protocols (Methods in Molecular Biology, No91), Jaroszeski and Heller, Eds., Humana Press, 1998; Current Protocolsin Cytometry, Robinson et al., eds, John Wiley & Sons, New York, N.Y.,2000. The readouts of selected parameters are capable of being realsimultaneously, or in sequence during a single analysis, as for examplethrough the use of fluorescent antibodies to cell surface molecules. Asan example, these can be tagged with different fluorochromes,fluorescent bead, tags, e.g. quantum dots, etc., allowing analysis of upto 4 or more fluorescent colors simultaneously by flow cytometry.Plug-flow flow cytometry that has the potential to automate the deliveryof small samples from unpressurized sources at rates compatible withmany screening and assay applications, may allow higher throughput,compatible with high throughput screening, Edwards et al. (1999)Cytometry 37:156-9.

[0072] Both single cell multiparameter and multicell multiparametermultiplex assays, where input cell types are identified and parametersare read by quantitative imaging and fluorescence and confocalmicroscopy are used in the art, see Confocal Microscopy Methods andProtocols (Methods in Molecular Biology Vol. 122.) Paddock, Ed., HumanaPress, 1998. These methods are described in U.S. Pat. No. 5,989,833issued Nov. 23,1999.

[0073] The quantitation of nucleic acids, especially messenger RNAs, isalso of interest as a parameter. These can be measured by hybridizationtechniques that depend on the sequence of nucleic acid nucleotides.Techniques include polymerase chain reaction methods as well as genearray techniques. See Current Protocols in Molecular Biology, Ausubel etal., eds, John Wiley & Sons, New York, N.Y., 2000; Freeman et al. (1999)Biotechniques 26(1):112-225; Kawamoto et al. (1999) Genome Res9(12):1305-12; and Chen et al. (1998) Genomics 51(3):313-24, forexamples.

[0074] Identifiers of individual cells, for example different cell typesor cell type variants, may be fluorescent, as for example labeling ofdifferent unit cell types with different levels of a fluorescentcompound, and the like. If two cell types are to be mixed, one may belabeled and the other not. If three or more are to be included, each maybe labeled to different levels of fluorescence by incubation withdifferent concentrations of a labeling compound, or for different times.As identifiers, of large numbers of cells, a matrix of fluorescencelabeling intensities of two or more different fluorescent colors may beused, such that the number of distinct unit cell types that areidentified is a number of fluorescent levels of one color, e.g.,carboxyfluorescein succinimidyl ester (CFSE), times the number offluorescence levels employed of the second color, e.g.tetramethylrhodamine isothiocyanate (TRITC), or the like, times thenumber of levels of a third color, etc. Alternatively, intrinsic lightscattering properties of the different cell types, or characteristics ofthe BioMAPs of the test parameters included in the analysis, can be usedin addition to or in place of fluorescent labels as unit cell typeidentifiers.

Data Analysis

[0075] The comparison of a BioMAP obtained from test cells, and areference BioMAP(s) is accomplished by the use, of suitable deductionprotocols, Al systems, statistical comparisons, etc. Preferably, theBioMAP is compared with a database of reference BioMAPs. Similarity toreference BioMAPs from normal cells, cells from similarly diseasedtissue, from cell lines with responses induced by assay combinationsinvolving known pathway stimuli or inhibitors, and the like, can providean initial indication of the cellular pathways activated in the testcells, and the responsiveness of the test cells to a therapeuticregimen.

[0076] A database of reference BioMAPs can be compiled. These databasesmay include reference BioMAPs from panels that include known agents orcombinations of agents that target specific pathways, as well asreferences from the analysis of cells treated under environmentalconditions in which single or multiple environmental conditions orparameters are removed or specifically altered. Reference BioMAPs mayalso be generated from panels containing cells with genetic constructsthat selectively target or modulate specific cellular pathways. In thisway, a database is developed that can reveal the contributions ofindividual pathways to a complex response.

[0077] The effectiveness of pattern search algorithms in classifyingBioMAPs can involve the optimization of the number of parameters andassay combinations. The disclosed techniques for selection of parametersprovide for computational requirements resulting in physiologicallyrelevant outputs. Moreover, these techniques for pre-filtering data sets(or potential data sets) using cell activity and disease-relevantbiological information improve the likelihood that the outputs returnedfrom database searches will be relevant to predicting agent mechanismsand in vivo agent effects.

[0078] For the development of an expert system for selection andclassification of biologically active drug compounds or otherinterventions, the following procedures are employed. For everyreference and test pattern, typically a data matrix is generated, whereeach point of the data matrix corresponds to a readout from a parameter,where data for each parameter may come from replicate determinations,e.g. multiple individual cells of the same type. As previouslydescribed, a data point may be quantitative, semi-quantitative, orqualitative, depending on the nature of the parameter.

[0079] The readout may be a mean, average, median or the variance orother statistically or mathematically derived value associated with themeasurement. The parameter readout information may be further refined bydirect comparison with the corresponding reference readout. The absolutevalues obtained for each parameter under identical conditions willdisplay a variability that is inherent in live biological systems andalso reflects individual cellular variability as well as the variabilityinherent between individuals.

[0080] Classification rules are constructed from sets of training data(i.e. data matrices) obtained from multiple repeated experiments.Classification rules are selected as correctly identifying repeatedreference patterns and successfully distinguishing distinct referencepatterns. Classification rule-learning algorithms may include decisiontree methods, statistical methods, naive Bayesian algorithms, and thelike.

[0081] A knowledge database will be of sufficient complexity to permitnovel test BioMAPs to be effectively identified and classified. Severalapproaches for generating a sufficiently encompassing set ofclassification patterns, and sufficiently powerfulmathematical/statistical methods for discriminating between them canaccomplish this.

[0082] A database can be compiled by preparing BioMAPs using differentcombinations of a plurality of biologically active factors, inconjunction with BioMAPs involving the use of known agents having knowneffects and/or the use of genetically modified cells, where the geneticmodification affects one or more of the pathways affected by one or moreof the factors used to create the phenotype. For example, if the cultureconditions selected to produce a specific in vitro reference patterncontain four biologically active agents, in addition to those present inthe basal conditions of the normal or basal environment, a BioMAP wouldbe generated from a panel of cells treated under all possiblecombinations of the 4 agents (15 assay conditions), typically usingconstant concentrations in each of the combinations. The extent of thedatabase associated with assay combinations to screen candidates forspecific phenotypes, e.g. indications, will vary with the nature of thephenotype, the amount of information desired, the complexity of thesystem, and the like.

[0083] The data from cells treated with specific drugs known to interactwith particular targets or pathways provide a more detailed set ofclassification readouts. Data generated from cells that are geneticallymodified using over-expression techniques and anti-sense techniques,permit testing the influence of individual genes on the phenotype.

[0084] As indicated, agents may be analyzed in the absence of anyfactors or with a limited number of factors. The assay is performed aspreviously described and the values of the parameters can be compared tothe BioMAP reflecting the values for the parameters of the physiologicstate of interest, the values of the parameters for the response to oneor more factors, and the basal response. In this way, the effect of theagent under physiological conditions can be evaluated. Similarly, onemay have datasets compiled from combinations of agents to determinetheir effect when combined on cell physiology.

[0085] A preferred knowledge database contains reference BioMAPscomprising data from optimized panels of cells, environments andparameters. For complex environments, data reflecting small variationsin the environment may also be included in the knowledge database, e.g.environments where one or more factors or cell types of interest areexcluded or included or quantitatively altered in, for example,concentration or time of exposure, etc.

Disease Markers

[0086] Cells from a clinical sample that are suspected of having amarker that is associated with or causative of disease can be analyzedfor the presence of genetic polymorphisms or other markers. Geneticcharacterization analyzes DNA or RNA, from any source, e.g. skin, cheekscrapings, blood samples, etc. The nucleic acids are screened for thepresence of a polymorphism of interest, e.g. SNPs, microsatellitemarkers, and the like.

[0087] A number of methods are available for analyzing nucleic acids forthe presence or absence of a specific sequence. Where large amounts ofDNA are available, genomic DNA is used directly. Analysis of genomic DNAmay use whole chromosomes or fractionated DNA, e.g. Southern blots, etc.Comparative Genomic Hybridization (CGH), as described in U.S. Pat. No.5,665,549, provides methods for determining the relative number ofcopies of a genomic sequence. The intensity of the signals from eachlabeled subject nucleic acid and/or the differences in the ratiosbetween different signals from the labeled subject nucleic acidsequences are compared to determine the relative copy numbers of thenucleic acid sequences as a function of position along the referencechromosome spread. Other methods for fluorescence in situ hybridizationare known in the art, for a review, see Fox et al. (1995) Clin Chem41(11):1554-1559.

[0088] Alternatively, the region of interest is cloned into a suitablevector and grown in sufficient quantity for analysis. Cells that expressgenes of interest may be used as a source of mRNA, which may be assayeddirectly or reverse transcribed into cDNA for analysis. The nucleic acidmay be amplified by conventional techniques, such as the polymerasechain reaction (PCR), to provide sufficient amounts for analysis. Theuse of the polymerase chain reaction is described in Saiki, et al.(1985) Science 239:487, and a review of techniques may be found inSambrook, et al. Molecular Cloning: A Laboratory Manual, CSH Press 1989,pp.14.2□14.33. Alternatively, various methods are known in the art thatutilize oligonucleotide ligation as a means of detecting polymorphisms,for examples see Riley et al. (1990) N.A.R. 18:2887-2890; and Delahuntyet al. (1996) Am. J. Hum. Genet. 58:1239-1246.

[0089] A detectable label may be included in an amplification reaction.Suitable labels include fluorochromes, e.g. fluorescein isothiocyanate(FITC), rhodamine, Texas Red, phycoerythrin, allophycocyanin,6-carboxyfluorescein (6-FAM),2′,7′-dimethoxy-4′,5′-dichloro-6-carboxyfluorescein (JOE),6-carboxy-X-rhodamine (ROX),6-carboxy-2′,4′,7′,4,7-hexachlorofluorescein (HEX), 5-carboxyfluorescein(5-FAM) or N,N,N′,N′-tetramethyl-6-carboxyrhodamine (TAMRA), radioactivelabels, e.g. ³²p, ³⁵S, ³H; etc. The label may be a two stage system,where the amplified DNA is conjugated to biotin, haptens, etc. having ahigh affinity binding partner, e.g. avidin, specific antibodies, etc.,where the binding partner is conjugated to a detectable label. The labelmay be conjugated to one or both of the primers. Alternatively, the poolof nucleotides used in the amplification is labeled, so as toincorporate the label into the amplification product.

[0090] The sample nucleic acid, e.g. genomic DNA, amplification productor cloned fragment, is analyzed by one of a number of methods known inthe art. The nucleic acid may be sequenced by dideoxy or other methods,and the sequence of bases compared to the sequence of genes of interest.Hybridization with the variant sequence may also be used to determineits presence, by Southern blots, dot blots, etc. The hybridizationpattern of a control and variant sequence to an array of oligonucleotideprobes immobilised on a solid support, as described in U.S. Pat. No.5,445,934, or in WO95/35505, may also be used as a means of detectingthe presence of variant sequences. Single strand conformationalpolymorphism (SSCP) analysis, denaturing gradient gel electrophoresis(DGGE), and heteroduplex analysis in gel matrices are used to detectconformational changes created by DNA sequence variation as alterationsin electrophoretic mobility.

[0091] Alternatively, where a polymorphism creates or destroys arecognition site for a restriction endonuclease, the sample is digestedwith that endonuclease, and the products size fractionated to determinewhether the fragment was digested. Fractionation is performed by gel orcapillary electrophoresis, particularly acrylamide or agarose gels.

[0092] Changes in the promoter or enhancer sequence that may affectexpression levels of genes of interest can be compared to expressionlevels of the normal allele by various methods known in the art. Methodsfor determining promoter or enhancer strength include quantitation ofthe expressed natural protein; insertion of the variant control elementinto a vector with a reporter gene such as β-galactosidase, luciferase,chloramphenicol acetyltransferase, etc. that provides for convenientquantitation; and the like.

[0093] Microsatellite linkage analysis may be performed alone, or incombination with direct detection of polymorphisms. The use ofmicrosatellite markers for genotyping is well documented. For examples,see Mansfield et al. (1994) Genomics 24:225-233; Ziegle et al. (1992)Genomics 14:1026-1031; Dib et al., supra. Microsatellite loci havenon-repetitive flanking sequences that uniquely identify the particularlocus, and a central repeat motif that is at least 2 nucleotides inlength, up to 7, usually 2-4 nucleotides in length. Repeats can besimple or complex. The number of repeats at a specific locus arepolymorphic in a population, thereby generating individual differencesin the length of DNA that lies between the repeats. The number will varyfrom at least 1 repeat to as many as about 100 repeats or more. Primerscan be used to amplify the region of genomic DNA that contains therepeats. Conveniently, a detectable label will be included in theamplification reaction. Multiplex amplification may be performed inwhich several sets of primers are combined in the same reaction tube.This is particularly advantageous when limited amounts of sample DNA areavailable for analysis. Conveniently, each of the sets of primers islabeled with a different fluorochrome. After amplification, the productsare size fractionated. Fractionation may be performed by gelelectrophoresis, particularly denaturing acrylamide or agarose gels. Aconvenient system uses denaturing polyacrylamide gels in combinationwith an automated DNA sequencer, see Hunkapillar et al. (1991) Science254:59-74. The automated sequencer is particularly useful with multiplexamplification or pooled products of separate PCR reactions. Capillaryelectrophoresis may also be used for fractionation. A review ofcapillary electrophoresis may be found in Landers, et al. (1993)BioTechniclues 14:98-111. The size of the amplification product isproportional to the number of repeats that are present at the locusspecified by the primers. The size will be polymorphic in thepopulation, and is therefore an allelic marker for that locus.

[0094] Screening for markers, e.g. surrogate markers for a diseasecondition, may be based on the functional or antigenic characteristicsof the protein. Various immunoassays may be used in screening.Functional protein assays are also effective screening tools, forexample by detecting the specific phosphatase, kinase, protease, orother enzymatic activity in a sample. Alternatively, changes inelectrophoretic mobility may be used.

[0095] Antibodies may be used in staining or in immunoassays. Forexample, detection may utilize staining of cells or histologicalsections, performed in accordance with conventional methods. Cells arepermeabilized to stain cytoplasmic molecules. The antibodies of interestare added to the cell sample, and incubated for a period of timesufficient to allow binding to the epitope, usually at least about 10minutes. The antibody may be labeled with radioisotopes, enzymes,fluorescers, chemiluminescers, or other labels for direct detection.Alternatively, a second stage antibody or reagent is used to amplify thesignal. Such reagents are well known in the art. For example, theprimary antibody may be conjugated to biotin, with horseradishperoxidase-conjugated avidin added as a second stage reagent.Alternatively, the secondary antibody conjugated to a flourescentcompound, e.g. flourescein, rhodamine, Texas red, etc. Final detectionuses a substrate that undergoes a color change in the presence of theperoxidase. The absence or presence of antibody binding may bedetermined by various methods, including flow cytometry of dissociatedcells, microscopy, radiography, scintillation counting, etc. Analternative method for diagnosis depends on the in vitro detection ofbinding between antibodies proteins in a lysate. A conventional sandwichtype assay may be used. Other immunoassays are also known in the art andmay find use as diagnostics. Ouchterlony plates provide a simpledetermination of antibody binding. Western blots may be performed onprotein gels or protein spots on filters, using a detection systemspecific for PC-1 as desired, conveniently using a labeling method asdescribed for the sandwich assay.

Endothelial Cells

[0096] The present invention is useful for classification of endothelialcells according to their physiologic state. Endothelial cells are foundin inflammatory tissues; they are highly responsive to environmentalstimuli; and they are a cell type for which primary cells can be readilyisolated and cultured. For example, vascular endothelial cellsparticipate in the inflammatory disease process by regulating the typeof leukocytes that are recruited to the target tissue. The specificityof recruitment is determined by the combinatorial expression of adhesionmolecules and chemokines. A number of factors are known to be associatedwith endothelial cells, such as EGF, FGF, VEGF, insulin, etc.,cytokines, such as the interleukins, including IL-1 IL-3, IL-4, IL-8 andIL-13; interferons, including IFN-α, IFN-β, IFN-γ; chemokines; TNF-α,TGFβ, proangiogenic and anti-angiogenic factors, etc. (See CurrentProtocols in Immunology, supra.).

[0097] Endothelial cells in inflammatory tissues from chronicinflammatory disease patients differ from endothelial cells in normaltissues by increased expression parameters including ICAM-1, E-selectin,IL-8 and HLA-DR [Nakamura S, Lab Invest 1993, 69:77-85; Geboes K,Gastroenterology 1992, 103:439-47; Mazzucchelli L, J Pathol 1996,178:201-6]. In addition, each of these parameters has been demonstratedto function in the inflammatory disease process. ICAM-1 and E-selectinare cell adhesion molecules that contribute to the localization andactivity of inflammatory cells including T cells, monocytes, andneutrophils. IL-8 is a neutrophil chemoattractant and HLA-DRparticipates in the activity of pathologic T cells. Other cell surfaceor secreted parameters include parameters that are known to be regulatedby factors, such as VCAM-1, which is induced on endothelial cells byTNF-α or IFN-γ; IL-10 and MIG which are induced on endothelial cells byIFN-γ; or GRO-α or ENA-78 which are induced on endothelial cells by IL-1and/or TNF-α [Goebeler M, J Invest Dermatol 1997, 108:445-51; Piali LEur J Immunol. 1998, 28:961-72].

[0098] The highly responsive nature of endothelial cells makes themparticularly useful in co-culture, such as with patient samples, astheir response due to factors from the patient sample or due tointeractions with patient samples can give specific informationregarding the state of the patient sample.

Leukocytes

[0099] Lymphokine-producing activated lymphocytes (CD45RO+, CD44hi,etc.) are a hallmark of inflammatory diseases including psoriasis,rheumatoid arthritis, Crohn's disease, ulcerative colitis, asthma, etc.Depending on the disease environment and tissue site, activatedlymphocytes can differ in their expression and function of adhesionmolecules and other receptors, as well as in their production of variouscytokines and other factors. The ability to selectively block lymphocyteactivation associated with the inflammatory disease without inhibitingor suppressing lymphocyte activation associated with the ability tofight infection and neoplasia is a goal of inflammatory drug therapy.

[0100] Specific homing and adhesion receptors, as well as chemokinereceptors, expressed by lymphocytes differentiating into effector andmemory cells target the involved regulatory and cytotoxic T cellpopulations, as well as B cells responsible for humoral immunity.Upregulation and modulation of homing receptor expression patterns isobserved when lymphocytes are activated in defined microenvironmentscomprising specific cytokines; and in some environments multiple homingreceptors (e.g., α₄β₇, the cutaneous lymphocyte antigen (“CLA”),inflammatory chernokine receptor such as CCR5 and CXCR3 and bonzo, etc.)are induced. Multiplex analysis of each of these homing receptorparameters, which may also be performed in conjunction with otherparameters in reflecting the cellular state of activation, can be usedto select immunomodulatory compounds capable of shifting patterns ofhoming receptor expression in a common microenvironment. Such modulatorsof lymphocyte targeting can be powerful immunosuppressives for localizedimmune pathologies, as in inflammatory bowel diseases, psoriasis,multiple sclerosis, arthritis, and the like; modulating patterns oflymphocyte homing/targeting molecules they would modulate in vivo immuneresponses therapeutically without the side effects associated withgeneralized immunosuppression.

[0101] The assay conditions for these cells include (1) known activationconditions ((combinations ofanti-CD3+IL-2+/−IL-4+/−IFN-γ+/−IL-12+/−anti-IL-4 or anti-IFN-γ). Suchconditions are given in: T Cell Protocols : Development and Activation(Methods in Molecular Biology, 134), Kearse, Ed., Humana Press, 2000).Assay combinations and reference BioMAPs are identified for a variety ofdiseases, including psoriasis, arthritis, Crohn's disease, ulcerativecolitis, asthma, etc.

[0102] The disease environment in psoriasis includes IL-12, IFN-γ andTNF-γ (Yawalker, 1998, J. Invest. Dermatol. 111:1053; Austin, 1999, J.Invest. Dermatol. 113:752), therefore an assay combination for psoriasiswill include one or more, usually at least two, and frequently all ofthese factors. Inflammatory T cells in psoriasis express high levels ofthe CLA antigen, a carbohydrate antigen related to Sialyl Lewis x (Berg,1991, J. Exp. Med. 174:1461; Picker, 1990, Am. J. Pathol. 136:1053).Therefore a parameter set for psoriasis will contain the CLA antigen.

[0103] The disease environment in Crohn's disease includes IL-1, TNF-α,IL-6, IL-8, IL-12, IL-18, and IFN-γ (Daig, 1996; Woywodt, 1994; Kakazu,1999; Pizarro, 1999; Monteleone, 1999), therefore an assay combinationfor Crohn's disease will include one or more of these factors, generallyincluding at least two of the IL factors, by themselves or incombination with at least one of IFN-γ and TNF-α. T cells ininflammatory bowel disease express high levels of the αEβ7 integrin(Elewaut, 1998, Scand J. Gastroenterol, 33:743), therefore the parameterset for inflammatory bowel diseases preferentially contains αEβ7

[0104] The disease environment in rheumatoid arthritis includes TNF-α,IL-1, IL-6, IL-10, IL-15, MIP1 β MCP-1, and TGF β (Robinson, 1995, Clin.Exp. Immunol. 101:398; Thurkow, 1997, J. Pathol. 181:444; Suzuki, 1999,Int. Immunol, 11:553), therefore an assay combination for arthritis-willinclude one or more of these factors, generally including at least twoof the IL factors and at least one of MIP1 and MCP-1. T cells inrheumatoid arthritis synovial fluid express CCR5 and CXCR3 (Suzuki,;1999; Qin, 1998, J. Clin. Invest. 101:746; Loetscher, 1998, Nature391:344), therefore the parameter set for rheumatoid arthritispreferentially contains CCR5 and CXCR3.

[0105] The disease environment in asthma includes IL-1β, IL-4, IL-5,IL-6 and GM-CSF (Miadonna, 1997; Walker, 1994), therefore, an assaycombination for asthma will contain one or more of these factors,generally including at least two of the IL factors and GM-CSF.

Macrophage

[0106] Peripheral blood monocytes, tissue macrophages and related cellscan be screened pharmacologically active compounds/interventions.Monocytes/macrophages in different physiological settings have alteredresponses. IL-4 reduces production of IL-10 in LPS stimulated bloodmonocytes but not in synovial monocyte/macrophages (Bonder (1999)Immunol. 96:529; Ju (1999) Int. Rev. Immunol. 18:485). In addition tobeing highly responsive to their environment, monocytes/macrophagesparticipate in a variety of disease processes, including inflammation,fibrosis, and wound healing, through their production of mediators,growth factors, phagocytosis and antigen presentation functions. Assaycombinations, e.g. IL-4 and other IL factors, M-CSF, and GM-CSF are usedin combination with each other or other factors associated with thephysiologic or disease environments of interest and readout parametersets are selected that allow different states to be distinguished.Readout parameters include integrins, adhesion molecules, and the like.

Mast Cell

[0107] The present invention can be applied to the classification ofmast cell activation, and the responsiveness of mast cells totherapeutic agents, e.g. in the treatment of allergy and asthma, wheremast cell products mediate disease pathology (Galli, 2000, Curr. Opin.Hematol. 7:32). Mast cells display altered responses depending on theirenvironment. The ability of mast cells to produce IL-3 and GM-CSF issignificantly increased in the presence of fibronectin or vitronectin(Kruger-Krasagakes, 1999, Immunology, 98:253). Mast cells inallergen-induced late-phase cutaneous reactions in atopic patientsexpress high levels of the high affinity IgE receptor compared with mastcells in control skin (Ying, 1998, Immunology 93:281). Assaycombinations including at least one of fibronectin and vitronectin aredeveloped that reflect physiologic or disease environments and readoutparameter sets, including at least one of IL-3, GM-CSF, andIgE-receptor, are selected that allow different states to bedistinguished. Reference patterns, held in a knowledge database includethose developed from the analysis of cells treated under environmentalconditions in which single components are removed, or with known drugsthat target specific pathways.

Cancer Applications

[0108] The invention is also useful for classification of cancer cellsand other associated cells present in tumors, e.g. endothelial cells,lymphocytes, etc., and for testing agents that have therapeuticactivity. Drug interactions are highly important in cancer therapy. Forexample, while steroids control the edema that occurs with glioma, theyalso interfere with chemotherapy efficacy. Cytotoxic drugs are a maintreatment for cancer and interference with the chemotherapy efficacy mayoffset the anti-tumor effect of an apoptosis inducer. On the other hand,synergy between individual drugs would be highly beneficial, perhapsallowing reduced doses of the individual drugs and reducing the sideeffects.

[0109] The present invention can be applied to the classification of themetastatic phenotypes of cancer cells. Metastatic cancers have alteredadhesive and invasive functions. Metastatic cancers are associated withcertain features including expression of various oncogenes, such asH-ras, increased levels of proteolytic enzymes, such as TPA (tissueplasminogen activator), production of osteopontin, and altered adhesionmolecule expression and function. For example, carcinomas preferentiallyexpress α6 β1 and less α2β1, α3β1, and α5β1 (Chambers 1993, Crit. Rev.Oncol. 4:95; Dedhar, 1995, Cancer Metastasis Rev. 14:165; Tuck, 1999,Oncogene 18:4237). Simultaneous multiplex analyses of normal and cancercell lines allows discrimination of agents that selectively modulate themetastatic phenotype.

[0110] There is a general inverse relationship between the degree ofcellular differentiation and the rate of cell proliferation in tumors.Several anti-cancer agents stimulate the differentiation and inhibitproliferation of malignant cells, including retinoids, various cytokinesand analogs of vitamin D (Bollag, 1994, J. Cell Biochem. 56:427).All-trans retinoic acid, an agent that induces differentiation, gives ahigh rate of complete clinical remission in the treatment of acutepromyelocytic leukemia (Tallman, 1994, Semin Hematol 31 (Suppl 5):38).Agents that stimulate differentiation are not easily detected usingtraditional in vitro assays of anticancer drug activity.

[0111] The present invention can be applied determine the effectivenesscompounds that induce apoptosis of tumor endothelial cells. Tumorendothelium differs from other endothelium by increased expression ofαvβ3. A set of conditions that induce apoptosis of these cells isevaluated and a set of parameters that defines a BioMAP diagnostic ofapoptosis is identified. Apoptotic conditions are identified as thosethat induce DNA laddering, and other well described features. Theseinclude simple culture conditions that contain one or more factors knownto induce or promote endothelial cell apoptosis in vitro, such asceremide, the combination of TNF-α and heat shock or sodium arsenite,TNF-α+IFN-γ, oxysterols; TNF-α in the presence of cyclohexamine, etc.(See Ruegg (1998) Nat. Med. 4:408). Parameters that may be included inthe selected set include a variety of molecules involved in adhesion andproteolysis (since a prominent feature of apoptotic endothelial cells istheir release from the vessel wall), those that can be modulated byindividual factors, such as E-selectin, ICAM-1, VCAM and HLA-DR, andmolecules or determinants known to be modulated with apoptosis such asCD95, ICAM-1, CD44, and carbohydrate determinants (Herbst, 1999, J. CellPhysiol. 181:295; Rapaport, 1999, Glycobiology 9:1337; Hirano (1999)Blood 93:2999; Thomas (1998) J. Immunol. 161:2195; Ma (1998) Eur. J.Hematol. 61:27; Pober (1998) Pathol. Biol. (Paris) 46:159).

Angiogenesis Inhibitors

[0112] The present invention can be applied to the classification ofcells with respect to potential for angiogenesis. Pharmacologicmodulation of angiogenesis has applications to the treatment of cancer,where vascularization of tumors contributes to cancer growth; forinflammatory conditions such as arthritis where neovascularizationsupports inflammatory cell influx; wound healing; and others. A numberof biologically active agents are known to induce or promoteangiogenesis including VEGF, FGF, IL-8, IL-4, various extracellularmatrix components, etc., where at least 2, usually at least 3 of thesefactors may be used in an assay combination. Vascularizing arthritisenvironments contain basic FGF and VEGF in addition to TNF-α, IL-1,IL-6, IL-10, IL-15, MIP1β and MCP-1 (Qu, 1995, Lab Invest., 73:339;Koch, J. Immunol. 1994, 152:4149; Robinson, 1995, Clin. Exp. Immunol.101:398; Thurkow, 1997, J. Pathol. 181:444; Suzuki, 1999, Int. Immunol,11:553). The disease environments of highly vascularized tumors includeshypoxia, VEGF, fibrinogen and TGF-β (Senger, 1994 Invasion Metastasis,95:385; Shweiki, 1992, Nature, 359:843). Parameters include adhesionmolecules, receptors, chemokines, etc., that are known to bedifferentially expressed by angiogenic endothelium at the disease sites.These may include the expression of functional forms of adhesionmolecules such as avβ3, VCAM, proteases, such as matrixmetalloproteinases, or other substances.

[0113] Kits. For convenience, the systems of the subject invention maybe provided in kits. The kits would include the appropriate additivesfor providing the simulation, reagents for measuring the parameters,software for preparing the BioMAP, and comparison BioMAPs with patientinformation and outcome. The factors will be selected that inconjunction with the cells would provide the desired physiological statesimulating the in vivo situation. The factors could be a mixture in theappropriate proportions or provided individually. For example, IL-1,TNF-α, and IFN-γ would be combined as a powder to be measured foraddition to the cell medium and labeled antibodies to parameters, suchas ICAM-1, VCAM-1 and E-selectin, in conjunction with second captureantibodies or using antibodies for homogeneous assays, where anotherreagent is present. The software will receive the results and create aBioMAP and will include data from other determinations of analogoussituations for comparison. The software can also normalize the resultswith the results from a basal culture and/or the basal culture includingthe factors.

[0114] It is to be understood that this invention is not limited to theparticular methodology, protocols, cell lines, animal species or genera,and reagents described, as such may vary. It is also to be understoodthat the terminology used herein is for the purpose of describingparticular embodiments only, and is not intended to limit the scope ofthe present invention which will be limited only by the appended claims.

[0115] As used herein the singular forms “a”, “and”, and “the” includeplural referents unless the context clearly dictates otherwise. Alltechnical and scientific terms used herein have the same meaning ascommonly understood to one of ordinary skill in the art to which thisinvention belongs unless clearly indicated otherwise.

[0116] The following examples are put forth so as to provide those ofordinary skill in the art with a complete disclosure and description ofhow to make and use the subject invention, and are not intended to limitthe scope of what is regarded as the invention. Efforts have been madeto ensure accuracy with respect to the numbers used (e.g. amounts,temperature, concentrations, etc.) but some experimental errors anddeviations should be allowed for. Unless otherwise indicated, parts areparts by weight, molecular weight is average molecular weight,temperature is in degrees centigrade; and pressure is at or nearatmospheric.

EXPERIMENTAL Example 1 Regulators of Endothelial Cell Responses toInflammation

[0117] The present invention is useful for identifying regulators ofinflammation using human endothelial cells as an indicator cell type. Aset of assay combinations that reproduces aspects of the response of theendothelial cells to different types of inflammatory processes isdeveloped in vitro.

[0118] Primary human umbilical vein endothelial cells (HUVEC) are used.Other cells that may replace HUVEC in the screen include primarymicrovascular endothelial cells, aortic or arteriolar endothelial cellsor endothelial cell lines such as EAhy926 or E6-E7 4-5-2G cells or humantelomerase reverse transcriptase-expressing endothelial cells (Simmons,J. Immunol., 148:267, 1992; Rhim, Carcinogenesis 19:673, 1998; Yang, J.Biol. Chem. 274:26141, 1999). 2×10⁴ cells/ml are cultured to confluencein EGM-2 (Clonetics). Other media that may replace EGM-2 include EGM(Clonetics) and Ham's F12K medium supplemented with 0.1 mg/ml heparinand 0.03-0.05 mg/ml endothelial cell growth supplement (ECGS) and 10%FBS, or medium M199 (Life Technologies, Inc.) containing 20% fetalbovine serum and 2 ng/ml basic fibroblast growth factor (Jaffe, J. Clin.Invest. 52:2745, 1973; Hoshi, PNAS 81:6413, 1984). The diseaseenvironment present in chronic inflammatory diseases, such as Crohn'sdisease, differs from the normal condition by increased presence ofmultiple biologically active agents including IL-1β, TNF-α, and IFN-γ(Woywodt, 1994; Kakazu, 1999). Other biologically active agents that maybe increased in chronic inflammatory disease environments include IL-4,IL-6, IL-8, IL-12, IL-13, IL-18, TGFbeta, and histamine, as well asactivated leukocytes and their products (Daig, 1996, Gut 38:216;Woywodt, 1994, Eur. cytokine Netw. 5:387; Kakazu, 1999 Am J.Gastroenterol. 94:2149; Pizarro, 1999, J. Immunol. 162:6829; Monteleone,1999, J. Immunol. 163:143; McClane, 1999 J Parenter Enteral Nutr 23:S20;Beck, 1999, Inflam. Bowel Dis. 5:44). Optimized assay combinations willcontain at least two, and preferably three, four or more of thesebiologically active agents. Concentrations of agents are standardaccording to the literature, typically at physiologic concentrations.Concentrations may also be determined experimentally as the amountrequired to saturate the relevant receptor. A useful feature of thepresent invention is that combinatorial effects of multiple factors areobserved over wide ranges of factor concentrations. Based on the factorsincluded in an assay combination, a set of parameters for including in aBioMAP are selected.

[0119] Selection of parameters is based on the following factors: 1)parameters that are modulated in vivo in the disease environment orcondition; 2) parameters that are modulated by one of the components inthe assay combination; 3) parameters that are modulated by more than oneof the components in the assay combination; 4) parameters that aremodulated by the combined action of two or more components in the assaycombination; 5) parameters that participate in the disease process, suchas validated disease targets; 6) cell surface and secreted molecules.Preferred parameters are functional and are downstream within signalingpathways, so as to provide information on effects of multiple pathways.For assay combinations containing the factors TNFα, IFN-γ and IL-1,parameters examined and chosen by these criteria include ICAM-1 (CD54),VCAM-1 (CD106), E-selectin (CD62E), IL-8, HLA-DR and MIG (CLCX9). Otherparameters of interest for including in a Biomap include: IP-10,Eotaxin-1, Eotaxin-3, MCP-1, RANTES, Tarc, CD31, alphavbeta3, andP-selectin (CD62P). Parameters examined but not selected include: CD34,CD40, CD9, CXCR2, CD95, fibronectin, HLA-ABC, GROalpha, MCP-4, TAPA-1,alphaVbeta5, VE-Cadherin, CD44, von Willebrand factor, CD141, 142, 143,and CD151. Parameters are not selected for inclusion in a BioMAP for thefollowing reasons: redundancy, function of parameter is not associatedwith disease pathology, function is upstream in a signaling pathway,parameter is not modulated in response to factors, modulation is notrobust or reproducible. Cell death in inflammation, involved for examplein cellular remodelling in healing, as well as the consequences oftoxicity, involves apoptosis. Parameters of interest also includeparameters indicative of cell damage and apoptosis including releasedcytoplasmic lactate dehydrogenase (LDH) or mitochondrial cytochrome c,appearance of APO2.7 epitope or active caspase-3 (Zhang, J. Immunol.,157:3980, 1996; Bussing, Cytometry 37:133, 1999). Parameters indicativeof cell proliferation are also of interest and include Ki-67 and PCNA(Landberg Cytometry, 13:230, 1992).

[0120] The experiments shown in FIG. 1A-1B illustrate the usefulness ofthe present invention in compound screeriing applications. FIG. 1A showsthe readout patterns from confluent cultures of HUVEC incubated witheither of IFN-γ (100 ng/ml), TNF-α (5 ng/ml), IL-1 (1 ng/ml), two ormore of these in combination, or basal medium for 24 hours. After 24hours, cultures are washed and evaluated for the presence of theparameters ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5),HLA-DR (6) and MIG (7) by cell-based ELISA as described (Melrose, J.Immunol. 161:2457, 1998). For this, plates are blocked with 1% Blottofor 1 hr, and treated with primary antibodies (obtained from Pharmingenand Becton Dickinson) at 1 ng/ml for 2 hr. After washing, secondaryperoxidase-conjugated anti-mouse IgG antibody (Promega) at 1:2500 isapplied for 45 min. After washing, TMB substrate (Kierkegaard & Perry)is added and color developed. Development is stopped by addition ofH₂SO₄ and the absorbance at 450 nm (subtracting the backgroundabsorbance at 600 nm) is read with a Molecular Dynamics plate reader.The relative expression levels of each parameter are indicated by the ODat 450 nm shown along the y-axis. The mean +/− SD from triplicatesamples is shown.

[0121]FIG. 1B shows a visual representation of the data from FIG. 1A,where the measurement obtained for each parameter is classifiedaccording to its relative change from the value obtained in theoptimized assay combination (containing IL-1+TNF-α+INF-γ), andrepresented by shaded squares. For each parameter and assay combination,the square is shaded by a checkerboard if the parameter measurement isunchanged (<20% above or below the measurement in the first assaycombination (IL-1+TNF-α+INF-γ)) or p>0.05, n=3; slanted lines indicatesthat the parameter measurement is moderately increased (>20% but <50%);white indicates the parameter measurement is strongly increased (>50%);vertical lines indicates that the parameter measurement is moderateddecreased (>20% but <50%); hatched lines indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first assay combination).

[0122] As shown in FIG. 1A, HUVEC cultured with IFN-γ for 24 hoursexpress increased levels of ICAM-1, HLA-DR and MIG, compared to cellscultured with media alone, as measured by cell-based ELISA. HUVECcultured with TNF-α for 24 hours express increased levels of cellsurface ICAM-1, VCAM-1, and E-selectin. HUVEC cultured in the presenceof both TNF-α and IFN-γ for 24 hours produce a combined phenotype whereHUVEC express increased levels of ICAM-1, VCAM-1, E-selectin, HLA-DR andMIG. This phenotype is more similar to the in vivo phenotype ofendothelial cells in chronic inflammation and moreover reflects thestimulation (and interaction) of two different known pathways ofinterest in regulation of inflammatory processes. Addition of IL-1 tothe assay combination containing TNF-α and IFN-γ further alters thephenotype resulting in increased levels of E-selectin and IL-8 (shown inFIG. 1A), in addition to the increased levels of ICAM-1, VCAM-1, HLA-DRand MIG. E-selectin and IL-8 are particularly correlated with diseasestage in chronic inflammatory diseases, including inflammatory boweldisease (MacDermott, 1999, J. Clin. Immunol. 19:266; Koizumi, 1992,Gastroenterology 1992103:840). Concentrations of IL-1β, TNF-α and IFN-γemployed and length of exposure are standard according to theliterature. Concentrations and exposure length are also testedexperimentally and conditions chosen to achieve an endothelial cellphenotype displaying multiple features of endothelial cells in chronicinflammatory diseases (e.g increased expression of ICAM-1, VCAM-1,E-selectin as well as HLA-DR and MIG). However, a particularly usefulfeature of of the invention is that the combined phenotype is observedover a wide range of concentrations of the individual biologicallyactive factors. Thus an assay combination containing IL-1, TNF-α andIFN-γ represents an optimized assay combination. This assay combinationis useful for screening for compounds that modulate aspects of IL-1,TNF-α or IFN-γ signaling pathways. In particular, it provides a usefulscreen for selecting compounds that are active when a particular targetpathway may be modified by the activity of other pathways or when thetarget is not known.

[0123] In subsequent panels one or more of IL-4, IL-6, IL-8, IL-12,IL-13, IL-18, TGFbeta, and histamine are applied; and/or neutralizingantibodies to autocrine factors such as IL-6, IL-1 and IL-8. Standardconcentrations of agents are employed as described in the literature.Based on the factors selected, a set of parameters for including in aBioMAP is selected.

[0124] Database of readout response patterns. A database of referenceBioMAPs is compiled for the optimized assay combination and parameterset of the example described in FIG. 1. These reference BioMAPs aredeveloped from assay combinations in which specific modifications of theoptimized assay combination are made. These modifications included: 1)elimination of one or more assay combination components, 2) addition ofcompounds or interventions to the assay combination. Biologicalresponses, particularly responses in primary human cells can displaysignificant variability from day to day and from donor to donor. Oneimportant aspect of the present invention is that while absolute amountsof parameters can vary substantially between assays, combinatorialresponses provide for less variability and the process of normalizationto produce a BioMAP provides cellular activity profiles that are robustand reproducible.

[0125] An inhibitor of TNF-α is an active compound in the optimizedassay combination described above. Addition of neutralizing anti-TNF-αantibodies to this assay combination results in reduced expressionlevels of ICAM-1, VCAM-1, E-selectin, IL-8, and MIG, and increasedexpression levels of CD31 (FIG. 2A). Confluent cultures of HUVEC cellsare treated with TNF-α (5 ng/ml)+IFNγ (100 ng/ml)+IL-1 (1 ng/ml) in thepresence or absence of neutralizing anti-TNF-α or control antibody (Goatanti-IgG). After 24 hours, cultures are washed and evaluated for thecell surface expression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8(4), CD31(5), HLA-DR (6) and MIG (7) by cell-based ELISA performed asdescribed in FIG. 1. In FIG. 2A, the relative expression of eachparameter is shown along the y-axis as average value of the OD measuredat 450 nm of triplicate samples. The mean +/− SD from triplicate samplesare, shown. * indicates p<0.05 comparing results obtained withanti-TNF-α to the control.

[0126]FIG. 3B, is a color-coded representation of the BioMAPs developedfrom the data shown in A. For each parameter and assay combination, thesquare is shaded by a checkerboard if the parameter measurement isunchanged (<20% above or below the measurement in the first assaycombination (IL-1+TNF-α+INF-γ)) or p>0.05, n=3; slanted lines indicatesthat the parameter measurement is moderately increased (>20% but <50%);white indicates the parameter measurement is strongly increased (>50%);vertical lines indicates that the parameter measurement is moderateddecreased (>20% but <50%); hatched lines indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first assay combination).

[0127] Inhibitors of NFκB, MAP kinases and non-steroidalantiinflammatory drugs are active compounds in the optimized assaycombination described above. FIG. 3A shows results of assaying confluentcultures of HUVEC cells treated with TNF-α (5 ng/ml)+IFN-γ (100ng/ml)+IL-1 (1 ng/ml) in the presence or absence of (A) 10 μM NHGA, 200μM PDTC or 9 μM PD098059 or (B) 125-500 μM ibuprofen. Compounds aretested at the highest concentration at which they are soluble, and donot result in cellular toxicity or loss of cells from the plate. After24 hours, cultures are washed and evaluated for the cell surfaceexpression of ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31(5), HLA-DR (6) and MIG (7) by cell-based ELIS performed as described inFIG. 1. A color-coded representation of the BioMAPs developed from thedata is shown. For each parameter and assay combination, the square isshaded by a checkerboard if the parameter measurement is unchanged (<20%above or below the measurement in the first assay combination(IL-1+TNF-α+INF-γ)) or p>0.05, n=3; slanted lines indicates that theparameter measurement is moderately increased (>20% but <50%); whiteindicates the parameter measurement is strongly increased (>50%);vertical lines indicates that the parameter measurement is moderateddecreased (>20% but <50%); hatched lines indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first assay combination).

[0128] In the present example, FIG. 3A shows how addition of the NFκBinhibitors nordihydroguaiaretic acid (NHGA) (Brennen, Biochem.Pharmacol., 55:965, 1998) or pyrrolidine dithiocarbamate (PDTC) (Boyle,Circulation, 98, (19 Suppl):II282, 1998) to the optimized assaycombination results in altered BioMAPs that are distinct from thealtered BioMAPs obtained with the p42/44 MAP kinase inhibitor, PD098059(Milanini, J. Biol. Chem. 273:18165, 1998). Active compounds that actwith a similar mechanism of action as NHGA and PDTC will give a BioMAPthat can be distinguished from active compounds that act with a similarmechanism of action as PD098059.

[0129] Obtaining BioMAPs from drug compounds tested at differentconcentrations also expands the usefulness of the database. In thepresent example, ibuprofen gives visually distinct BioMAPs when testedat 500, 250 and 125 μM, as shown in FIG. 3B, although regressionanalysis indicates they are highly related (correlation coefficientsderived from the primary data range between 0.96-0.99).

[0130] Reference BioMAPs from assay combinations that include known drugcompounds, agents, or with other specific modifications are developedfor inclusion in a database. Biomaps from these assay combinations aredeveloped so as to expand the usefulness of the database. Table 1 showsa list of agents or specific modifications evaluated, includingN-acetylcysteine (Faruqui, Am. J. Physiol. 273(2 Pt 2):H817, 1997), thecorticosteroids dexamethasone and prednisolone, echinacea, AA861 (Lee,J. Immunol. 158, 3401, 1997), apigenin (Gerritsen, Am. J. Pathol.147:278, 1995), nordihydroguaiaretic acid (NHGA) (Brennen, Biochem.Pharmacol., 55:965, 1998), phenylarsine oxide (PAO) (Dhawan, Eur. J.Immunol. 27:2172, 1997), pyrrolidine dithiocarbamate (PDTC) (Boyle,Circulation, 98, (19 Suppl):11282, 1998), PPM-18 (Yu, Biochem. J.,328:363, 1997), the non-steroidal anti-inflammatory drug (NSAID)buprofen, SB 203580, PD098059 (Milanini, J. Biol. Chem. 273:18165,1998), AG126 (Novogrodsky, Science 264, 1319, 1994), and neutralizinganti-TNF-α antibody. Color-coded representations of the resultingBioMAPs are shown. Confluent cultures of HUVEC cells are treated withTNF-α (5 ng/ml)+INF-γ (100 ng/ml)+IL-1 (1 ng/ml) in the presence orabsence of agents or buffers at the concentrations indicated in Table 1.Compounds are obtained from commercial sources and prepared in asuitable buffer (water, base media, DMSO, methanol or ethanol). After 24hours, cultures are washed and evaluated for the cell surface expressionof ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5), HLA-DR(6) and MIG (7) by cell-based ELISA performed as described in FIG. 1. Acolor-coded representation of the resulting BioMAPs developed from thedata is shown. For each parameter and assay combination, the square iscolored light gray if the parameter measurement is unchanged (<20% aboveor below the measurement in the control assay combination(IL-1+TNF-α+INF-γ)) or p>0.05, n=3; white/gray hatched indicates thatthe parameter measurement is moderately increased (>20% but <50%); whiteindicates the parameter measurement is strongly increased (>50%);black/gray hatched indicates that the parameter measurement ismoderately decreased (>20% but <50%); black indicates that the parametermeasurement is strongly decreased (>50% less than the level measured inthe first. Control assay combinations for each agent include anappropriate concentration of the diluent buffer. TABLE 1 REFERENCEBioMAPs. Readout Parameters Inhibitor Class UID Compound Conc. Units 1 23 4 5 6 7 Antioxidant 181 N-acetylcysteine 5.00 μM

Antioxidant 182 N-acetylcysteine 2.50 μM

Antioxidant 183 N-acetylcysteine 1.25 μM

Antioxidant 184 N-acetylcysteine 1.25 μM

Corticosteroid 717 Dexamethazone 12.50 μM

Corticosteroid 716 Dexamethazone 6.25 μM

Corticasteroid 715 Dexamethazone 3.10 μM

Corticasteroid 301 Dexamethazone 2.00 μM

Corticosteroid 302 Dexamethazone 1.00 μM

Corticosteroid 303 Dexamethazone 0.50 μM

Corticosteroid 241 Prednisolone 160.00 μM

Corticosteroid 242 Prednisolone 160.00 μM

Corticosteroid 243 Prednisolone 80.00 μM

Corticosteroid 244 Prednisolone 40.00 μM

Natural Product 91 Echinacea 2.27 &

Natural Product 94 Echinacea 2.27 %

Natural Product 92 Echinacea 1.13 %

Natural Product 93 Echinacea 0.57 %

NFκB 4 AA861 20.00 μM

NFκB 5 AA861 20.00 μM

NFκB 6 AA861 20.00 μM

NFκB 701 AA861 20.00 μM

NFκB 19 Apigenen 8.10 μM

NFκB 20 Apigenen 6.00 μM

NFκB 21 Apigenen 5.00 μM

NFκB 202 Nordihydroguaiaretic acid (NHGA) 10.00 μM

NFκB 203 Nordihydroguaiaretic acid (NHGA) 10.00 μM

NFκB 204 Nordihydroguaiaretic acid (NHGA) 10.00 μM

NFκB 719 Nordihydroguaiaretic acid (NHGA) 6.00 μM

NFκB 205 Nordihydroguaiaretic acid (NHGA) 5.00 μM

NFκB 718 Nordihydroguaiaretic acid (NHGA) 0.63 μM

NFκB 720 PAO 50.00 μM

NFκB 231 PDTC 200.00 μM

NFκB 233 PDTC 200.00 μM

NFκB 234 PDTC 200.00 μM

NFκB 725 PDTC 100.00 μM

NFκB 726 PDTC 100.00 μM

NFκB 235 PDTC 100.00 μM

NFκB 232 PDTC 50.00 μM

NFκB 724 PDTC 50.00 μM

NFκB 236 PDTC 50.00 μM

NFκB 728 PPM-18 2.50 μM

NFκB 727 PPM-18 2.00 μM

NFκB 735 PPM-18 2.00 μM

NSAID 131 Ibuprofen 500.00 μM

NSAID 132 Ibuprofen 500.00 μM

p38 MAPK 730 SB 203580 80.00 μM

p38 MAPK 729 SB 203580 40.00 μM

p42/44 MAPK 221 PD098059 18.70 μM

p42/44 MAPK 222 PD098059 9.30 μM

p42/44 MAPK 223 PD098059 9.30 μM

p42/44 MAPK 224 PD098059 9.00 μM

p42/44 MAPK 723 PD098059 9.00 μM

p42/44 MAPK 225 PD098059 4.60 μM

p42/44 MAPK 722 PD098059 2.25 μM

p42/44 MAPK 721 PD098059 0.56 μM

Tyr Kinase 733 AG126 25.00 μM

Tyr Kinase 702 AG126 25.00 μM

Tyr Kinase 734 AG126 25.00 μM

Antibody 712 Anti-TNF 5.00 μg/ml

Antibody 713 Anti-TNF 5.00 μg/ml

Antibody 711 Anti-TNF 4.00 μg/ml

Antibody 710 Anti-TNF 1.67 μg/ml

Antibody 709 Anti-TNF 0.55 μg/ml

Antibody 708 Anti-TNF 0.40 μg/ml

Antibody 707 Anti-TNF 0.04 μg/ml

Antibody 714 Anti-TNF-R (Act) 5.00 μg/ml

N/A 520 Control

N/A 521 Control

N/A 522 Control

N/A 523 Control

N/A 524 Control

N/A 525 No IL1

N/A 526 No IL1

N/A 527 No IL1

N/A 531 No TNF

N/A 532 No TNF

N/A 533 No TNF

N/A 515 NoIL1IFNγ

N/A 516 NoIL1IFNγ

N/A 517 NoIL1IFNγ

N/A 518 NoIL1IFNγ

N/A 519 NoIL1IFNγ

N/A 510 NoTNFIFNγ

N/A 511 NoTNFIFNγ

N/A 512 NoTNFIFNγ

N/A 513 NoTNFIFNγ

N/A 514 NoTNFIFNγ

N/A 505 No IL1TNF

N/A 506 No IL1TNF

N/A 507 No IL1TNF

N/A 508 No IL1TNF

N/A 509 No IL1TNF

N/A 500 No IL1TNFIFNγ

N/A 501 No IL1TNFIFNγ

N/A 502 No IL1TNFIFNγ

N/A 503 No IL1TNFIFNγ

N/A 504 No IL1TNFIFNγ

[0131]FIG. 3C shows a visual representation of how these referenceBioMAPs can be compared by pattern similarity and cluster analysis.Readout patterns are analyzed by hierarchical clustering techniques, andare visualized as a tree diagram in which a) each terminal branch point,represents the readout pattern from one assay combination in oneexperiment; b) the length of the vertical distance from the upperhorizontal line (no change and control patterns) to the termini arerelated to the extent of difference in the readout pattern from thecontrol environment pattern; and c) the distance along the branches fromone terminal pattern value to another reflects the extent of differencebetween them. Similar patterns are thus clustered together.

[0132] Compounds that inhibit the NFκB pathway, such as the5-lipoxygenase inhibitors AA861 and nordihydroguaiaretid acid (NHGA)(Lee, J. Immunol. 158, 3401, 1997), pyrrolidine dithiocarbamate (PDTC)(Boyle, Circulation 98: (19 Suppl):11282, 1998), PPM-18, a chemicallysynthesized naphthoquinone derivative (Yu, Biochem. J., 328:363, 1997)and the flavenoid apigenin (Gerritsen, Am. J. Pathol. 147:278, 1995),have similar reference BioMAPs and cluster together. Thecorticosteroids, dexamethasone and prednisolone also yield a set ofrelated reference BioMAPs that are distinct from those of NFκB pathwayinhibitors.

[0133] An important feature of BioMAP analysis is how BioMAPs resultingfrom different concentrations of active agents, although they differfrom one another (see FIG. 3C), remain clustered together in the clusteranalysis. This can be seen in FIG. 3C where the BioMAPs that result fromtesting PD098059 at different concentrations remain in the same cluster(indicating-their similarity with one another), although BioMAPsresulting from testing PD098059 at higher concentrations are found inthe lower branches of the cluster, indicating higher degree ofdifference (lower correlation coefficient) from the BioMAPs resultingfrom no intervention or inactive agents. Thus BioMAP analysis is usefulfor distinguishing the mode of action of a variety of compounds.

[0134] This example demonstrates that the BioMAPs are useful indistinguishing the mode of action of candidate compounds, so as to knowwhether combinations of candidate compounds act on the same pathway ordifferent pathways, their combined effect on parameter levels andwhether they provide synergy or act in an antagonistic way.

[0135] These assay combinations are highly useful for testing a largenumber of compounds or agents with many different or unknown mechanismsof action. This procedure balances the desirability of a screening assaythat provides in depth information, with the advantages of an assay thatis also amenable for scale-up high throughput screening. The assaycombinations described are useful for general screening for compoundswith anti-inflammatory or proinflammatory activity. Assay combinationstailored for specific inflammatory diseases are developed by alteringthe combination of input biologically active agents. For example,specific assay combinations useful for inflammatory diseases that aremore Th2-like in nature, such as asthma or allergy should includeadditional agents, such as IL-4 or IL-13, that are preferably found inthose disease conditions, and so forth.

Example 2 BioMAP Assays for Characterizing T Cell Responses—TCell-Endothelial Cell Co-Cultures

[0136] The present invention is applied for characterizing patienttissue samples. A set of assay combinations that includes patientsamples is utilized to characterize the status of patient samples.

[0137] Primary human umbilical vein endothelial cells and the human Tcell line, KIT255 are used. Other cells that may replace HUVEC in thescreen include primary microvascular endothelial cells or aorticendothelial cells. 2×10⁴ HUVEC/ml were cultured to confluence inEGM-2-(Clonetics). Other media that may replace EGM-2 include EGM(Clonetics) and Ham's F12K medium supplemented with 0.1 mg/ml heparinand 0.03-0.05 mg/ml endothelial cell growth supplement (ECGS) and 10%FBS, or medium M199 (Life Technologies, Inc.) containing 20% fetalbovine serum and 2 ng/ml basic fibroblast growth factor (Jaffe, J. Clin.Invest. 52:2745, 1973; Hoshi, PNAS 81:6413, 1984). One or more of thefollowing are then applied: 10³ KIT255 cells, IL-2 (10 ng/ml), IL-12 (10ng/ml), and or base media. After 24 hours, cultures are washed andevaluated for the presence of the parameters ICAM-1 (1), VCAM-1(2),E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6) and MIG (7) by cell basedELISA as described in FIG. 1 and shown in FIG. 4. In this figure,analysis performed by cell based ELISA provides readout patterns thatcombine HUVEC and T cell readouts. FIG. 4 demonstrates that the BioMAPsderived from assay combinations containing KIT255 cells+/−IL-2 and IL-12can be distinguished. Other cells that may replace KIT255 include humanperipheral blood samples including peripheral bllod leukocytes, humanperipheral blood T cells, human peripheral blood CD3+ cells, and thehuman T cell lines Jurkat and HUT78. In subsequent panels, one or moreof: PHA, IL-6, IL-7, activating antibody to CD3, activating antibody toCD28, IL-1, TNF-α, IFN-γ, IL-4, IL-13 or neutalizing antibodies to IL-1,IL-2, TNF-α, IFN-γ, IL-12 and/or IL-4 are applied. Other markers ofinterest for adding to the BioMAP include MCP-1, IP-10, cutaneouslymphocyte antigen (CLA), CXCR3, CCR3, TNF-α, IFN-γ, IL-2, IL-4,alpha4beta7, alphaEbeta7, and L-selectin. Analytical methods thatdistinguish T cells from endothelial cells, such as flow cytometry orimage analytical techniques can be employed. A database of BioMAPs isgenerated from a panel of assay combinations that includeanti-inflammatory drug compounds including inhibitors of T cellactivation and/or T cell proliferation, calcineurin inhibitors, etc. arescreened and BioMAPs are generated that reflect the changes in themarkers with the different agents. Such agents are given in ThePharmacologic Basis of Therapeutics. The BioMAPs with the known agentsare used to compare to candidate immunomodulatory agents. This allowsthe recognition of the pathway(s) the candidate test agent acts on, bycomparing the changes in the level of the specific markers for knownagents affecting known pathways and the changes observed with thecandidate test agent. In addition to further add to the utility of theBioMAP, one may include in the database reference BioMAPs generated fromassay panels containing cells with genetic constructs that selectivelytarget or modulate specific cellular pathways (e.g. NFAT, calcineurin,NFκB, MAP kinase, etc), or cells that contain known genetic mutations,e.g. Jurkat cell tines that lack Ick, CD45, etc. (Yamasaki, J. Biol.Chem. 272:14787, 1997).

Example 3 BioMAP Assays for Characterizing Patients from Blood Samples

[0138] The present invention is useful for monitoring patients forcharacterizing their inflammatory status.

[0139] Primary human umbilical vein endothelial cells (HUVEC) are used.Other cells that may replace HUVEC in the screen include primarymicrovascular endothelial cells, aortic or arteriolar endothelial cellsor endothelial cell lines such as EAhy926 or E6-E7 4-5-2G cells or humantelomerase reverse transcriptase-expressing endothelial cells (Simmons,J. Immunol., 148:267, 1992; Rhim, Carcinogenesis 19:673, 1998; Yang, J.Biol. Chem. 274:26141, 1999). 2×10⁴ cells/ml are cultured to confluencein base media, EGM-2 (Clonetics). One or more of the following are thenapplied: human blood cells (prepared from buffy coats obtained fromcitrated patient blood samples), washed and diluted {fraction (1/16)}),IL1 (1 ng/ml), TNFα (5 ng/ml), IFNγ (100 ng/ml) and or base media. After24 hours, cultures are washed and evaluated for the presence of theparameters ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8 (4), CD31 (5),HLA-DR (6), CD40 (8) and MCP-1 (9) by cell based ELISA. In FIG. 5,analysis performed by cell based ELISA provides readout patterns thatcombine HUVEC and blood cell readouts. FIG. 5A demonstrates that thereadout patterns derived from assay combinations containing endothelialcells and blood cells+/−IL-1, TNFα and IFNγ can be distinguished. FIG.5B demonstrates that the readout patterns derived from assaycombinations containing endothelial cells and either IL-1 (A), TNF (B),IFNγ (C), IL-1+TNF+IFNγ (D) or no exogenous cytokine (E) are distinctwith and without addition of blood cells. These assay combinations areuseful for monitoring the status of patients and demonstrates that theseassay combinations may be employed to monitor the status of inflammatorypathways in patient blood samples.

[0140] Other cells that may replace washed human peripheral blood cellsare purified or partially purified blood cell subsets such as humanperipheral blood T cells, human peripheral blood CD3+ cells, B cells,neutrophils. In subsequent panels, one or more of: PHA, ConA, activatingantibody to CD3, bacterial superantigens, activating antibody to CD28,IL-2, IL-4, IL-12, IL-13 or neutalizing antibodies to IL-1, IL-2, TNF-α,IFN-γ, IL-12 and/or IL-4 are applied. Other markers of interest foradding to the BioMAP include IP-10, cutaneous lymphocyte antigen (CLA),CXCR3, CCR3, TNF-α, IFN-γ, IL-2, IL-4, alpha4beta7, alphaEbeta7, andL-selectin. Analytical methods that distinguish T cells from endothelialcells, such as flow cytometry or image analytical techniques can beemployed. A database of BioMAPs is generated from a panel of assaycombinations that include anti-inflammatory drug compounds includingcorticosteroids, inhibitors of T cell activation and/or T cellproliferation, and inhibitors of calcineurin, TNF-α, IL-1, etc. arescreened and BioMAPs are generated that reflect the changes in themarkers with the different agents. Such agents are given in ThePharmacologic Basis of Therapeutics. BioMaps derived from blood samplesfrom normal humans are used to compare BioMAPs derived from samplesobtained from patients. In this way the inflammatory status of patientscan be assessed. This allows the recognition of the pathway(s) that areactive or inactive in the patient cells by comparing the changes in thelevel of the specific markers for known agents affecting known pathwaysin normal human cells and the changes observed with the patient cells.

[0141] Patient groups for which this would be of interest includepatients on immunosuppressive therapy such as transplant patients; andpatients with inflammatory or autoimmune disease in treatment withtherapies such as non-steroidal anti-inflammatories, methotrexate,cyclosporin, TNFα-antagonists; as well as otherwise immune compromisedpatients such as patients suffering from HIV infection, cancer, etc.

Example 4 BioMAPs for Characterization of Patient Cells with GeneticModifications

[0142] The present invention is useful for characterizing patients withgenetic differences. The present examples describes how the inventionallows differentiating and characterization of cells from patients withgenetic differences. In this example, Jurkat T cells are employed.Jurkat cells are a human T cell line originally isolated from a patientwith leukemia (Schneider, Int. J. Cancer 19:621, 1977). A genetic mutantJurkat cell line lacking the 13 chain of the TCR has been described(Ohashi, Nature 316:606, 1985). Primary human umbillical veinendothelial cells (HUVEC) are also used. Other cells that may replaceHUVEC in the screen include primary microvascular endothelial cells,aortic or arteriolar endothelial cells or endothelial cell lines such asEAhy926 or E6-E7 4-5-2G cells or human telomerase reversetranscriptase-expressing endothelial cells (Simmons, J. Immunol.,148:267, 1992; Rhim, Carcinogenesis 19:673, 1998; Yang, J. Biol. Chem.274:26141, 1999). 2×10⁴ HUVEC/ml are cultured to confluence in basemedia, EGM-2 (Clonetics). One or more of the following are then applied:2×10⁴ Jurkat cells or Jurkat mutants, superantigen (staphylococcalenterotoxin B, 20 ng/ml), IL1 (1 ng/ml), TNFα (5 ng/ml), IFN-γ (100ng/ml) and or base media. After 24 hours, cultures are washed andevaluated for the presence of the parameters ICAM-1 (1), VCAM-1 (2),E-selectin (3), IL-8 (4), CD31 (5), HLA-DR (6), MIG (7), CD40 (8) andMCP-1 (9) by cell

[0143] A database of BioMAPs is generated from a panel of assaycombinations that include normal Jurkat T cells in the presence andabsence of each biologically active factor; and reference drugs oragents including anti-inflammatory drug compounds including inhibitorsof T cell activation and/or T cell proliferation, calcineurininhibitors, inhibitors of signaling pathways such as NFAT, calcineurin,NFκB, MAP kinases, etc. are screened and BioMAPs generated that show thechanges in the markers with the different agents. Many agents are givenin The Pharmacologic Basis of Therapeutics. The BioMAPs with the knownagents are used to compare to BioMAPs generated from mutant Jurkatcells. This allows the recognition of the pathway(s) altered in themutant cells, by comparing the changes in the level of the specificmarkers for known drugs affecting known pathways in normal cells and thechanges observed with the mutant cellst. BioMAPs prepared with Jurkat Tcells lacking the TCRO can be readily distinguished BioMAPs preparedfrom normal Jurkat cells.

[0144] This application would be useful for characterizing patients thathave genetic differences contributing to their susceptibility to diseaseor responsiveness to drugs.

Example 5 BioMAPs for Characterization of Patient Cells with GeneticModifications—Genetically Modified Mice

[0145] The following example demonstrates the utility of the inventionin differentiating and catagorizing cells from patients with geneticdifferences. In this example, lymphocytes isolated from spleens ofgene-deficient mice, such as TNFα-deficient mice (TNFα−/−; Marino, PNAS94:8093, 1997) and primary human umbilical vein endothelial cells(HUVEC) are employed. Other cells that may replace HUVEC in the screeninclude primary microvascular endothelial cells or aortic endothelialcells. 2×104 HUVEC/ml are cultured to confluence in EGM-2 (Clonetics).Other media that may replace EGM-2 include EGM (Clonetics) and Ham'sF12K medium supplemented with 0.1 mg/ml heparin and 0.03-0.05 mg/mlendothelial cell growth supplement (ECGS) and 10% FBS, or medium M199(Life Technologies, Inc.) containing 20% fetal bovine serum and 2 ng/mlbasic fibroblast growth factor (Jaffe, J. Clin. Invest. 52:2745, 1973;Hoshi, PNAS 81:6413, 1984). One or more of the following are thenapplied: 2×10⁴ spleen cells from TNFα−/−mice (Marino, PNAS 94:8093,1997) or normal mice, superantigen (staphylococcal enterotoxin B, 20ng/ml), IL1 (1 ng/ml), TNFα (5 ng/ml), IFN-γ (100 ng/ml), and or basemedia. After 24 hours, cultures are washed and evaluated for thepresence of the parameters ICAM-1 (1), VCAM-1 (2), E-selectin (3), IL-8(4), CD31 (5), HLA-DR (6), CD40 (8) and MCP-1 (9) by cell based ELISA.

[0146] A database of BioMAPs is generated from a panel of assaycombinations that include normal murine spleen cell's and HUVEC in thepresence and absence of each biologically active factor; and referencedrugs or agents including anti-inflammatory drug compounds includinginhibitors of T cell activation and/or T cell proliferation, calcineurininhibitors, inhibitors of signaling pathways such as NFAT, calcineurin,NFκB, MAP kinases, etc. are screened and BioMAPs generated that show thechanges in the markers with the different agents. Many agents are givenin The Pharmacologic Basis of Therapeutics. The BioMAPs with the knownagents are used to compare to BioMAPs generated from mutant mouse cells.This allows the recognition of the pathway(s) that are altered in themutant mouse cells, by comparing the changes in the level of thespecific markers for known drugs affecting known pathways from normalmice and the changes observed with mutant mouse cells.

[0147] In subsequent panels, one or more of: PHA, IL-6, IL-7, activatingantibody to CD3, activating antibody to CD28, IL-2, IL-12, IFN-γ, IL-4,IL-13 or neutralizing antibodies to IL-1, IL-2, TNF-α, IFN-γ, IL-12and/or IL-4 are applied.

[0148] This application would be useful for characterizing patients thathave genetic differences contributing to their susceptibility to diseaseor responsiveness to drugs.

Example 6 BioMAPs for Characterization of Patients with Cancer

[0149] Cancers vary widely in their etiologies and responsiveness totherapy, even for patients with cancers of the same type and stage.While there are many mechanisms that contribute to the cancer phenotype,all cancers result in part from genetic alterations that result in lossof the control of cell growth. Because so many factors act to promoteand regulate cell growth, the mechanisms responsible in individualpatients and, therefore, the appropriate treatments for individualpatients can differ. Evaluating patient tumor cells in BioMAP assays istherefore useful for characterizing patients. In this example, the humanbreast cell lines MCF-7, UACC-812 and HCC38 are used to illustrate theapplication. MCF-7 expresses the estrogen receptor; UACC-812 is negativefor the estrogen receptor, but positive for Her-2/neu antigen, and MCC38does not express either. 2×10⁵ cells/ml are cultured in RPMI medium 10%FBS. Other media that may replace RPMI include Dulbecco's ModifiedEagle's Medium containing 20% FBS. Following overnight serum starvationone or more the following are then applied for 24 hours: estrogen (10⁻⁷M), antibody to Her-2/neu, epidermal growth factor (10 ng/ml) and FGF (2ng/ml). In subsequent panels one or more of IGF-I (5 nM), TNF-α (100ng/ml), IFN-γ (200 U/ml), IL-13 (30 ng/ml), TGF-β (10 ng/ml), IL-1β (10ng/ml) and IL-6; and/or neutralizing antibodies to autocrine factors,IL-1, TGF-β or the receptor IGF-R I, are added to the initial threefactors or may replace one of the three factors. Standard concentrationsof agents are employed as described in the literature (Jackson, JBC273:9994, 1998; He, PNAS 97:5768, 2000). BioMAPs are generated for theparameters ICAM-1 (CD54), EGF-R, MCP-1, E-cadherin, HLA-DR (CD74), CD44,carcinoembryonic antigen (CEA, CD66e) and α₅β₁. Other markers ofinterest for adding to the BioMAP include HLA-I, poly-Ig-receptor, IL-8,CD40, CA-19-9, CD95, α₂β₁, α₃β₁, α₆β₁, α₆β₄, α_(v), laminin 5,urokinase-type plasminogen activator receptor (uPAR), and TNFR-I.Parameters of interest also include parameters indicative of cell damageand apoptosis including released cytoplasmic lactate dehydrogenase (LDH)or mitochondrial cytochrome c, appearance of APO2.7 epitope or activecaspase-3 (Koester, Cytometry, 33:324, 1998; Zhang, J. Immunol.,157:3980, 1996; Bussing, Cytometry 37:133, 1999). Parameters indicativeof cell proliferation are also of interest and include Ki-67 and PCNA(Landberg, Cytometry, 13:230, 1992).

[0150] BioMAPs generated for MCF-7, UACC-812 and HCC38 arecharacteristic of the pathways active in each cell type and distinguishthe responsiveness of cells to estrogen and/or Her-2/neu ligands andother factors.

[0151] A database of BioMAPs is generated from a panel of assaycombinations that include a panel of breast cancer cell lines with thedifferentiation-inducing agent calcitriol, and known anti-cancer agents,anti-estrogens, DNA synthesis inhibitors, nucleoside analogs,topoisomerase inhibitors, and microtubule function inhibitors arescreened and a BioMAP generated that shows the changes in the markerswith the different anti-cancer agents. Such compounds are given inWeinstein, 1997, and The Pharmacologic Basis of Therapeutics. TheBioMAPs with cell lines are used to compare to patient tumor samples.This allows the recognition of the pathway(s) active in the patienttumor cells, by comparing the changes in the level of the specificmarkers foreknown drugs affecting known pathways and the changesobserved with the patient cells.

[0152] This application would be useful in characterizing patientsamples vis-a-vis responsiveness either to particular therapies, such asanti-estrogen therapy (e.g. tamoxifen) or therapy directed towards theHer-2/neu pathway (e.g. Herceptin).BioMAP

[0153] Although the invention has been described with reference to theabove examples, it will be understood that modifications and variationsare encompassed within the spirit and scope of the invention.Accordingly, the invention is limited only by the following claims.

What is claimed is:
 1. A method of preparing a biomap for theclassification of a patient sample according to pathways associated witha disease state, the method comprising: contacting said patient samplein a test cell culture with a plurality of factors in an amount andincubating for a time sufficient to induce a plurality of pathwaysactive in said cell culture; measuring at least four parametersassociated with said plurality of pathways and comparing the measurementof said at least four parameters with the measurement from a controlcell culture, and recording said measurements of said at least fourparameters to produce a biomap, wherein said biomap is indicative of thepathways that are active in said cell culture.
 2. The method accordingto claim 1, wherein said patient sample comprises cells, and wherein theresponse of said cells is measured for said at least four parameters. 3.The method according to 1 wherein said patient sample comprises fluidsor extracts of tissues, and wherein said fluids or extracts of tissuesare added to non-patient indicator cells provided in said cell culture.4. The method according to claim 1, wherein said cell culture comprisespatient cells, non-patient indicator cells, or a mixture thereof.
 5. Themethod according to claim 1, wherein said patient sample is distributedin a panel of cell culture assay combinations, wherein at least one ofsaid assay combinations is a control cell culture differing in at leastone component from said test cell culture; wherein said component can bea factor, a biologically active agent or other environmental condition.6. The method according to claim 1, wherein said test cell culturecomprises a therapeutic agent, and wherein said biomap is indicative ofthe responsiveness of said patient tissue sample to said therapeuticagent.
 7. The method according to claim 1, wherein said patient tissuesample comprises two or more distinct types of cells.
 8. The methodaccording to claim 7, wherein said distinct types of cells are selectedfrom the group consisting of endothelial cells, tumor cells,lymphocytes, monocytes, epithelial cells, neoplastic cells and mastcells.
 9. The method according to claim 1, wherein cells in said patientsample are separated according to phenotype prior to said contactingstep.
 10. The method according to claim 3, wherein factors in saidpatient sample are separated according to biochemical or immunologiccriteria prior to said contacting step.
 11. The method according toclaim 1, further comprising the step of analyzing said patient tissuesample for the presence of nucleic acid polymorphisms.
 12. The methodaccording to claim 1, further comprising the step of correlating saidbiomap with patient history and clinical diagnosis.